JP6664585B2 - Information processing apparatus, information processing method, and information processing program - Google Patents

Description

  The present invention relates to an information processing device, an information processing method, and an information processing program.

  2. Description of the Related Art Conventionally, a technique for providing various information such as contents to a user is known. Further, there is known a technique for providing information to a user as information for determination. For example, there has been provided a data judgment support system technology that enables an investor or the like to easily make an investment judgment. For example, in such a technique, time-series data of a first value indicating an event and time-series data of a second value indicating an event different from the event or data in which events are arranged in time series are displayed. By doing so, it assists the user in making an investment.

JP 2014-167688 A

  However, in the above-described conventional technology, it may be difficult to provide appropriate information to the user. For example, if the comparison is not effective in a time series, it is difficult to provide appropriate information to the user. For example, in comparison in time series, it may be difficult to determine whether the content of a certain content is true or false.

  The present application has been made in view of the above, and has as its object to provide an information processing apparatus, an information processing method, and an information processing program that provide appropriate information to a user.

  An information processing apparatus according to the present application determines an acquisition unit that acquires content-related information related to content, based on the content-related information acquired by the acquisition unit, whether the content satisfies a condition regarding fake nice. A determining unit that determines whether the content satisfies the condition by the determining unit and is fake opinion information serving as a material for determining whether the content corresponds to the fake nice, and a terminal device used by a user. And a providing unit that provides fake opinion information displayed together with the content to the terminal device.

  According to an aspect of the embodiment, it is possible to provide appropriate information to a user.

FIG. 1 is a diagram illustrating an example of information processing according to the embodiment. FIG. 2 is a diagram illustrating a configuration example of the information processing system according to the embodiment. FIG. 3 is a diagram illustrating a configuration example of the information processing apparatus according to the embodiment. FIG. 4 is a diagram illustrating an example of a provider information storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of the content information storage unit according to the embodiment. FIG. 6 is a diagram illustrating an example of an individual score information storage unit according to the embodiment. FIG. 7 is a diagram illustrating an example of the determination information storage unit according to the embodiment. FIG. 8 is a diagram illustrating an example of the true / false result information storage unit according to the embodiment. FIG. 9 is a flowchart illustrating an example of information processing according to the embodiment. FIG. 10 is a flowchart illustrating an example of information processing according to the embodiment. FIG. 11 is a diagram illustrating an example of display of fake opinion information according to the embodiment. FIG. 12 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device.

  Hereinafter, an information processing apparatus, an information processing method, and an embodiment (hereinafter, referred to as “embodiment”) for implementing an information processing program according to the present application will be described in detail with reference to the drawings. The information processing apparatus, the information processing method, and the information processing program according to the present application are not limited by the embodiment. In the following embodiments, the same portions are denoted by the same reference numerals, and redundant description will be omitted.

(Embodiment)
[1. Information processing)
First, an example of information processing according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of information processing according to the embodiment. The example of FIG. 1 illustrates a case where the information processing apparatus 100 determines whether or not each content satisfies a condition regarding fake nice based on content-related information related to the content. Here, the fake news may be news (content) including erroneous information, false information that does not exist, information that is not true, or incorrect information. Further, the fake news is not limited to the above, and may be, for example, various contents including information that may cause the viewed user to make a mistake. The content may include information intended to cause a mistake. Although the example of FIG. 1 shows a case where the content is a news article, the content may be any content as long as the authenticity of the content is important. Each content is provided by a content provider that provides the content (hereinafter, may be simply referred to as “provider”). Further, the example of FIG. 1 illustrates a case where the information processing apparatus 100 provides fake opinion information to the user based on the determination result to determine whether the content is fake nice.

[Configuration of information processing system]
Prior to the description of the processing illustrated in FIG. 1, the information processing system 1 illustrated in FIGS. 1 and 2 will be described. As shown in FIG. 2, the information processing system 1 includes a terminal device 10, a provider device 20, and an information processing device 100. The terminal device 10, the provider device 20, and the information processing device 100 are communicably connected via a predetermined network N by wire or wirelessly. FIG. 2 is a diagram illustrating a configuration example of the information processing system according to the embodiment. Note that the information processing system 1 illustrated in FIG. 2 may include a plurality of terminal devices 10, a plurality of provider devices 20, and a plurality of information processing devices 100.

  The terminal device 10 is an information processing device used by a user. The terminal device 10 is realized by, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like. The example illustrated in FIG. 1 illustrates a case where the terminal device 10 is a smartphone used by a user. In the following, the terminal device 10 may be referred to as a user. That is, in the following, a user can be read as the terminal device 10. Specifically, FIG. 1 illustrates a case where the terminal device 10 is a smartphone used by a user identified by the user ID “U1” (hereinafter, may be referred to as “user U1”).

  The provider device 20 is an information processing device used by a content provider. The provider device 20 may be used by any entity as long as it is a content provider, and is used by various providers such as companies and individuals. The provider device 20 is realized by, for example, a smartphone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, or the like. FIG. 1 shows a case where the provider device 20 is a notebook PC.

  Further, in the example illustrated in FIG. 1, the provider device 20 will be described as the provider devices 20-1 to 20-4 according to the provider that uses the provider device 20. For example, the provider device 20-1 is the provider device 20 used by the provider (provider CP11) identified by the provider ID “CP1”. The provider device 20-1 is an information processing device used by an administrator of the medium A which is the provider CP11. When described as “provider CP * (* is an arbitrary numerical value)”, it indicates that the provider is the provider identified by the provider ID “CP *”. For example, when "provider CP11" is described, the provider is the provider identified by the provider ID "provider CP11". In the following, the provider devices 20-1 to 20-4 will be referred to as the provider device 20 when they are described without particular distinction.

  The information processing apparatus 100 is an information processing apparatus that determines whether or not a content satisfies a fake nice condition based on content-related information related to the content. For example, the information processing apparatus 100 is an information processing apparatus that provides the terminal device 10 with fake opinion information that serves as a material for determining whether the content is fake nice based on the determination.

  From here, specific processing will be described with reference to FIG. In the example of FIG. 1, the information processing apparatus 100 acquires the content CT11 of the provider CP11 from the provider apparatus 20-1 (step S11-1). For example, the providing source CP11 transmits the content CT11 to the information processing device 100 using the providing source device 20-1. When the content is described as “content CT * (* is an arbitrary numerical value)”, it indicates that the content is the content identified by the content ID “CT *”. For example, when the content is described as content CT11, it indicates various information such as content information such as character information and image information included in the content identified by the content ID “CT11”, information indicating a provider, and category information. I do.

  Further, the information processing apparatus 100 acquires the content CT12 of the provider CP12 from the provider apparatus 20-2 (step S11-2). Further, the information processing apparatus 100 acquires the content CT13 of the provider CP13 from the provider apparatus 20-3 (step S11-3). Further, the information processing apparatus 100 acquires the content CT14 of the provider CP14 from the provider apparatus 20-4 (step S11-4). For example, the providing sources CP12 to CP14 transmit the contents CT12 to CT14 to the information processing device 100 using the providing devices 20-2 to 20-4, respectively.

  Steps S11-1 to S11-4 are for describing the processing, and any of steps S11-1 to S11-4 may be performed first, and each of steps S11-1 to S11-4 may be performed. May be performed a plurality of times. For example, the information processing apparatus 100 may acquire the content of each provider by performing each step S11 a plurality of times at a predetermined timing. Hereinafter, when steps S11-1 to S11-4 are described without distinction, they are collectively referred to as step S11.

  Then, the information processing device 100 registers the contents CT11 to CT14 acquired in step S11 (step S12). The information processing device 100 stores the contents CT11 to CT14 in the storage unit 120 (see FIG. 3). In the example of FIG. 1, the information processing apparatus 100 stores the contents CT11 to CT14 and information extracted from the contents CT11 to CT14 in the content information storage unit 122.

  The content information storage unit 122 illustrated in FIG. 1 has items such as “content ID”, “content information”, “provider ID”, “category”, “quoted content”, and “content”. Although not shown in FIG. 1, the content information storage unit 122 stores information on the date and time when each content is created.

  “Content ID” indicates identification information for identifying the content. “Content information” indicates the content identified by the corresponding content ID. In the example of FIG. 1, the content information is indicated by an abstract code such as “CDT11”, but each content information may include specific information of the content such as character information and image information included in the article. For example, as the content information, information corresponding to the content shown in parentheses such as “article A” and “article B” is stored.

  "Provider ID" indicates identification information for identifying the provider of the corresponding content. “Category” indicates classification information based on the content of the content. The “quoted content” indicates the content from which the corresponding content is generated. The quoted content referred to here may include other content that is quoted in the content or other content that is an information source for the content of the content. "Content" indicates the specific content of the corresponding content. For example, the information processing apparatus 100 extracts an important keyword (topic) from character information included in the content. Note that the information processing apparatus 100 may extract a topic from character information by appropriately using various conventional methods such as topic analysis (analysis). For example, the information processing apparatus 100 may extract a topic from the character information by appropriately analyzing the character information using a natural language processing technique such as morphological analysis. Further, for example, the information processing apparatus 100 may determine whether the content is positive or negative for the topic based on the syntactic relationship between the extracted topic and a keyword indicating topic affirmation or negation. . Then, the information processing apparatus 100 stores information indicating whether the content is positive or negative for the topic in the “content”.

  In the example of FIG. 1, the content CT11 is an article A provided by the provider CP11. The content CT11 indicates that the content is classified into the category “politics”. The content CT11 indicates that there is no quoted content. The content CT11 indicates that the content is positive about the tax increase after the election. That is, the content CT11 indicates that the content is a news article about the tax increase after the election.

  Then, the information processing apparatus 100 calculates a score of each content (hereinafter, also referred to as “fake score”) (step S13). For example, the information processing device 100 calculates a fake score of the contents CT11 to CT14. In the example of FIG. 1, the information processing apparatus 100 calculates a fake score of the contents CT11 to CT14 based on the information stored in the individual score information 123.

  “Determination element ID” in the individual score information storage unit 123 shown in FIG. 1 indicates identification information for identifying each determination element. “Determination element” in the individual score information storage unit 123 illustrated in FIG. 6 indicates the content of the determination element identified by the corresponding determination element ID. “Individual score” in the individual score information storage unit 123 illustrated in FIG. 1 indicates an individual score of each determination element.

  In the example of FIG. 1, the judgment element (judgment element JE11) identified by the judgment element ID “JE11” indicates that there is a content creation date. The judgment element JE11 indicates that a content without a creation date is assigned the individual score “0.2” as being likely to be fake news.

  In the example of FIG. 1, the judgment element identified by the judgment element ID “JE12” (judgment element JE12) indicates that evidence is cited. The judgment element JE12 indicates that the content without the evidence citation is assigned the individual score “0.5”, assuming that the content may be fake news. The judgment element (judgment element JE13) identified by the judgment element ID “JE13” indicates whether or not there is a difference between the contents of the other provider and the contents. The determination element JE13 indicates that the content having a difference from the content of the other provider is assigned the individual score “7” as being likely to be fake news. Note that the information processing device 100 may calculate an individual score, or may obtain an individual score from another information processing device. The calculation of the individual score will be described later.

  For example, the information processing device 100 calculates a score (fake score) using the following equation (1).

_{y = ω 1 · x 1 +} ω 2 · x 2 + ω 3 · x 3 ··· + ω N · x N ··· (1)

“ _N ” in “ω _N ” and “x _N ” in the right side of the above equation (1) indicates an arbitrary number. For example, “N” indicates the number of judgment elements. “Y” in the left side of the above equation (1) corresponds to the score output by the model. For example, “y” indicates a score (fake score) used to determine whether or not it is fake news.

In the above equation (1), “x” corresponds to a judgment factor (feature). For example, “x ₁ ” in the above equation (1) corresponds to the determination element “No creation date”. In this case, when the input content does not have a creation date, “x ₁ ” becomes “1”. If the input content has a creation date, “x ₁ ” becomes “0”.

For example, for example, “x ₂ ” in the above formula (1) corresponds to the judgment element “no evidence quote”. In this case, if there is no quotation of evidence in the input content, “x ₂ ” becomes “1”. Also, when the input content includes a quote of evidence, “x ₂ ” is “0”. For example, for example, “x ₃ ” in the above equation (1) corresponds to the determination element “difference from other providers”. In this case, when the input content has a difference in content from the content of another provider, “x ₂ ” becomes “1”. If the input content does not differ from the content of the other provider, “x ₂ ” is “0”.

In the above equation (1), “ω” is the weight of “x”, and indicates the individual score of the corresponding judgment element. For example, “ω ₁ ” in the above equation (1) is the weight (individual score) of “x ₁ ”, “ω ₂ ” is the weight (individual score) of “x ₂ ”, and “ω ₃ ” Is the weight (individual score) of “x ₃ ”. Note that the above is an example, and the information processing apparatus 100 calculates (generates) the individual score information by any method as long as the information about the individual score can be calculated based on the content-related information related to the content. Is also good.

  In the example of FIG. 1, the information processing apparatus 100 may use information indicating the degree of trust of the provider of each content stored in the provider information storage unit 121. “Credit (fake rate)” shown in the provider information storage unit 121 in FIG. 1 indicates the credit of the provider identified by the corresponding provider ID. For example, “credibility (fake rate)” indicates a ratio of content corresponding to fake news among contents provided by the provider. For example, when the credit (fake rate) is “5”, it indicates that the probability that the content provided by the provider is fake news is 5%. In this case, the smaller the value of the credibility (fake rate) of the provider, the more the provider can be trusted. In the example of FIG. 1, the trustworthiness of the provider CP11 is “2” and the trustworthiness of the provider CP12 is “0”, which indicates that the trust of the provider CP12 is more reliable than that of the provider CP11. Note that the information processing apparatus 100 may use not only the fake rate but also various information as information indicating the trustworthiness of the provider.

  For example, in the example shown in FIG. 4, the provider (provider CP1) identified by the provider ID “CP1” indicates that the name is “A medium” and the type is “newspaper”. The provider CP1 indicates that the credit (fake rate) is “2” and the probability that the content provided by the provider CP1 is fake news is 2%.

  For example, the determination element JE13, which is a determination element “difference from another provider”, includes a content that is different from the content of another provider whose credibility (fake rate) is less than a predetermined threshold. Indicates that it is determined that there is a difference between the content and the content.

In the example of FIG. 1, the information processing apparatus 100 determines that the content of the determination element JE13 is different from the content of another provider whose credit (fake rate) is less than “0.5” when the content is different from the content of another provider. It is determined that there is a difference between the content and the content. Here, among the contents CT11 to CT14, a certain content CT11 is only the content of “tax increase after election = positive” and the content of the other providers CP12 to CP14 whose credit (fake rate) is less than “0.5”. The content of CT11 to CT14 is “tax increase after election = denial”. Therefore, the information processing device 100 determines that the content CT11 corresponds to the determination element JE13. Therefore, the information processing apparatus 100 sets “x ₃ ” corresponding to the determination element JE13 to “1” for the content CT11 in the above equation (1).

  Through the processing described above, the information processing apparatus 100 calculates the fake score of each content as shown in the determination information storage unit 124 in FIG. In the example of FIG. 1, the information processing apparatus 100 calculates a fake score of each content based on Expression (1), content information of each content, and the like.

  “Content ID” in the determination information storage unit 124 shown in FIG. 1 indicates identification information for identifying a content. “Fake score” in the determination information storage unit 124 shown in FIG. 1 indicates a fake score of the content identified by the corresponding content ID. For example, the score stored in the “fake score” indicates the degree of possibility that the corresponding content is fake news.

  In the example of FIG. 1, the information processing device 100 calculates the fake score of the content CT11 as “15”. Further, the information processing device 100 calculates the fake score of the content CT12 as “0.02”. The information processing device 100 calculates the fake score of the content CT13 as “0.5”. Further, the information processing device 100 calculates the fake score of the content CT14 as “1”.

  Then, the information processing apparatus 100 determines whether or not a condition regarding fake nice is satisfied (step S14). For example, when one content satisfies a condition related to fake nice, the information processing apparatus 100 considers that the one content may be fake news (hereinafter, may be described as “possible fake”). judge. For example, when one content does not satisfy the condition regarding fake nice, the information processing device 100 does not have a possibility that the one content is fake news (hereinafter, may be described as “no fake possibility”). Is determined.

  For example, when the fake score of the content is equal to or more than a predetermined threshold (hereinafter, also referred to as a “threshold for determination”), the information processing apparatus 100 determines that the content has fake possibility. In the example of FIG. 1, when the fake score of the content is equal to or greater than the determination threshold “10”, the information processing apparatus 100 determines that the content has the possibility of fake.

  For example, since the fake score “15” of the content CT11 is equal to or greater than the determination threshold “10”, the information processing apparatus 100 determines that the content CT11 has a fake possibility. Further, since the fake score “0.02” of the content CT12 is less than the determination threshold “10”, the information processing apparatus 100 determines that the content CT12 has no fake possibility. Since the fake score “0.5” of the content CT13 is less than the determination threshold “10”, the information processing apparatus 100 determines that the content CT13 is not fake. Further, since the fake score “1” of the content CT14 is less than the determination threshold “10”, the information processing apparatus 100 determines that the content CT14 is not fake-possible. As described above, the information processing apparatus 100 determines that the content CT11 has the possibility of fake, and determines that the contents CT12 to CT14 have no possibility of fake. Then, the information processing apparatus 100 provides fake opinion information indicating the fake possibility of each of the contents CT11 to CT14 based on the determination together with the content.

  The information processing device 100 acquires a content request from the terminal device 10 used by the user U1 (Step S13). In FIG. 1, the terminal device 10 requests the content from the information processing device 100 according to the operation of the user U1.

  Then, the information processing device 100 determines content to be provided to the user U1 in response to a content request from the terminal device 10 (Step S16). In addition, the information processing apparatus 100 determines the content to be provided to the user U1 by appropriately using various types of information. In FIG. 1, for simplicity of description, the information processing apparatus 100 transmits the content CT11 to the user U1. The content to be provided shall be determined. For example, the information processing apparatus 100 may determine the content to be provided to the user U1 based on the attribute information of the user U1. For example, when the user U1 is a user who is interested in politics, the information processing apparatus 100 may determine content belonging to the category “politics” to be content to be provided to the user U1. Further, the information processing apparatus 100 may determine not to provide the content determined to have the possibility of fake. In this case, the information processing apparatus 100 may determine a content other than the content CT11 determined to have fake possibility as the content to be provided to the user U1.

  In the example of FIG. 1, the information processing apparatus 100 adds information to the content CT11 determined as the content to be provided to the user U1 (step S17). The information processing apparatus 100 adds information to the content CT11 as information for determining whether the content CT11 is fake news. For example, the information processing apparatus 100 adds the opinion information INF11 including the fake score “15” and the information indicating the possibility of fake to the information provided to the user U1. The information processing apparatus 100 adds the opinion information INF11 as information to be provided to the user U1 together with the content information CDT11 (article A) of the content CT11 as shown in the content to be provided DC11.

  Thereafter, the information processing device 100 provides the terminal device 10 with the content CT11 and the fake score “15” and the opinion information INF11 indicating that there is a possibility of fake (step S18). The information processing device 100 transmits to the terminal device 10 the content CT11, the fake score “15”, and the fake opinion information INF11 indicating the possibility of fake. Then, the terminal device 10 that has received the content CT11 and the fake opinion information INF11 displays the received information (step S19). The terminal device 10 displays the content CT11 and the fake opinion information INF11. In the example of FIG. 1, the terminal device 10 displays the fake opinion information INF51 in an area AR11 located near the content CT11. Specifically, the terminal device 10 displays the content CT11 that allows the tax increase after the election of the XX newspaper, and the fake opinion information INF51 indicating that the content may be fake (suspicious). I do.

  As described above, the information processing apparatus 100 provides the terminal device 10 with the content to be provided and the fake opinion information indicating whether the content of the content is a fake. Thus, the user who has received the information can browse the content together with the fake opinion information that is a material for determining whether the content is fake news. Therefore, the user can browse the content in consideration of information on the authenticity of the content. Therefore, the information processing device 100 can provide appropriate information to the user.

[1-1. Judgment)
In the example of FIG. 1, the information processing apparatus 100 determines whether or not the content has a fake possibility based on a comparison between a fake score, which is the sum of individual scores of each determination element, and a determination threshold value. Determine whether there is any possibility. However, the information processing apparatus 100 is not limited to the above, and may determine whether the content has the possibility of fake or not with the possibility of fake by various methods.

[1-1-1. Applicable to specific judgment factors)
When a certain content corresponds to a specific determination factor, the information processing apparatus 100 may determine that the content has fake possibility. For example, if the content of a certain provider is different from the content of another provider, the information processing apparatus 100 may determine that the content has fake possibility. For example, when the content of one provider is different from the content of another provider that is more reliable than the one provider, the information processing apparatus 100 may determine that the content has fake possibility.

  For example, when the content of one provider is different from the content of another provider having higher creditworthiness than the one provider, the information processing apparatus 100 may determine that the content has fake possibility. . That is, when the content of one provider is different from the content of another provider having a lower degree of trust than the one provider, the information processing apparatus 100 may determine that the content has fake possibility. . For example, if the content of one provider is different from the content of another provider whose fake rate is lower than that of one provider, the information processing apparatus 100 may determine that the content has fake possibility. Good. For example, when the content of one provider is different from the content of a plurality of (for example, 5) other providers, the information processing apparatus 100 may determine that the content has fake possibility.

  For example, when a certain content corresponds to the determination element JE13 “difference in content from the content of another provider”, the information processing device 100 may determine that the content has fake possibility. For example, when a content corresponds to the determination element JE13 “difference in content from the content of another provider”, the information processing apparatus 100 determines that the content has the possibility of fake regardless of the fake score of the content. May be.

[1-1-2. Information on quoted content]
Further, the information processing apparatus 100 may determine whether the content has a fake possibility or not, using information on the quoted content, which is another content cited by the content. For example, if it is determined that the quoted content of one content is fake news, the information processing apparatus 100 may determine that the one content has fake possibility. For example, when the cited content of one content is the content CT1 (see FIG. 8) that has been determined to be fake news, the information processing apparatus 100 determines that the one content has fake possibility. Is also good.

  Further, for example, when the quoted content of one content has the possibility of fake news, the information processing apparatus 100 may determine that the one content has the possibility of fake news. In the example of FIG. 1, the information CT 100 may determine that the content CT21 has the fake possibility because the content CT11 which is the cited content of the content CT21 has the possibility of fake news.

  For example, the information processing apparatus 100 may calculate a fake score of the content by using a determination element related to the quoted content of the content. For example, the information processing apparatus 100 may calculate the fake score of the content by using the individual score of the determination element regarding the quoted content of the content.

  For example, the information processing apparatus 100 may calculate the fake score of the content by using a determination element (hereinafter, referred to as “determination element JEX”) regarding whether the quoted content of the content may be fake news. For example, the information processing apparatus 100 may calculate the fake score of the content using the individual score of the determination element JEX.

  For example, when the quoted content of the content is fake news, the information processing apparatus 100 may determine that the content corresponds to the determination element JEX. For example, when the quoted content of the content is likely to be fake news, the information processing apparatus 100 may determine that the content corresponds to the determination element JEX. In this case, the information processing apparatus 100 may add the individual score of the determination element JEX to the fake score of the content.

[1-1-3. Source information)
Further, the information processing apparatus 100 may determine whether the content has the possibility of fake or not with the possibility of fake using the information of the provider of the content. For example, the information processing apparatus 100 may calculate a fake score of the content by using a determination element regarding a provider of the content. For example, the information processing apparatus 100 may calculate the fake score of the content by using the individual score of the determination element regarding the provider of the content.

  For example, the information processing apparatus 100 may calculate the fake score of the content by using a determination factor regarding whether the provider of the content is credible (referred to as “determination element JEY”). For example, the information processing apparatus 100 may calculate the fake score of the content using the individual score of the determination element JEY.

  For example, when the credibility of the content provider is poor, the information processing apparatus 100 may determine that the content corresponds to the determination element JEY. For example, when the credibility of the provider of the content is equal to or more than a predetermined threshold (provider threshold), the information processing apparatus 100 may determine that the content corresponds to the determination element JEY. That is, when the fake rate of the provider of the content is equal to or more than the predetermined threshold (the threshold for the provider), the information processing apparatus 100 may determine that the content corresponds to the determination element JEY. In this case, the information processing apparatus 100 may add the individual score of the determination element JEY to the fake score of the content.

[1-2. Calculation of individual score)
As described above, the information processing apparatus 100 may generate (calculate) the individual score of the determination element used for calculating the fake score in the example of FIG. For example, the information processing apparatus 100 may derive (calculate) the individual score of each determination element using the content information stored in the truth result information storage unit 125 (see FIG. 8).

  For example, the true / false result information storage unit 125 in FIG. 8 stores various types of information regarding contents that have been determined to be fake news among contents provided in the past. For example, the true / false result information storage unit 125 stores various types of information on the content for which true / false (authenticity) has been determined. Therefore, the information processing apparatus 100 receives information corresponding to each discrimination element extracted from the content information in the true / false result information storage unit 125 as input, and sets information indicating whether or not the fake indicated in the confirmed fake result is the correct answer information. , An individual score may be calculated.

  For example, the information processing apparatus 100 may derive (calculate) each discriminant element as a feature (feature amount) and the weight of each discriminant element as an individual score. For example, the information processing apparatus 100 calculates an individual score by performing learning using information of the content stored in the truth result information storage unit 125 as learning data (teacher data). For example, the information processing apparatus 100 generates a model by a learning process (model generation) using the information of the content stored in the truth result information storage unit 125, and thereby the feature amount (determination element) in the model. May be calculated as individual scores.

  For example, the information processing apparatus 100 may calculate an individual score for a judgment element by learning the weight (individual score) of each feature (judgment element) using the above equation (1).

  The information processing apparatus 100 may calculate individual score information of each judgment element by learning the weight (individual score) of each feature (judgment element) using the content determined to be a fake as a positive example. For example, the information processing apparatus 100 may calculate individual score information of each determination element using the content CT1 determined to be fake news in the truth result information storage unit 125 in FIG. 8 as a positive example. For example, when the content information CDT1 of the content CT1 is input, the information processing apparatus 100 performs the learning process such that the score output by the model outputs a score equal to or greater than a predetermined threshold (for example, “10”). Do. For example, when the content CT1 is targeted, the information processing apparatus 100 learns that the value (score) of “y” in the above equation (1) is equal to or greater than a determination threshold (for example, “10”). Perform processing.

  Further, for example, the information processing apparatus 100 may calculate the individual score information of each determination element using the content CT2 determined as not fake news in the truth result information storage unit 125 in FIG. 8 as a negative example. Good. For example, when the content information CDT2 of the content CT2 is input, the information processing apparatus 100 performs the learning process such that the score output by the model becomes a score (for example, “0”) smaller than a predetermined threshold. Do. For example, when the content CT2 is targeted, the information processing apparatus 100 sets the value (score) of “y” in the above equation (1) to a value smaller than the determination threshold (for example, “0”). The learning process is performed as described above.

  Also, for example, the information processing apparatus 100 may calculate individual score information of each determination element using the content CT3 determined as not fake news in the truth result information storage unit 125 in FIG. 8 as a negative example. Good. For example, when the content information CDT3 of the content CT3 is input, the information processing apparatus 100 performs a learning process such that the score output by the model becomes a score (for example, “0”) smaller than a predetermined threshold. Do. For example, when the content CT3 is targeted, the information processing apparatus 100 sets the value (score) of “y” in the above equation (1) to a value smaller than the determination threshold (for example, “0”). The learning process is performed as described above.

  For example, the information processing apparatus 100 may calculate an individual score for each content category. That is, the information processing apparatus 100 may generate a model for each content category. In the above example, the information processing apparatus 100 may calculate the individual score for the category “politics” using the contents CT1 and CT2 to which the category “politics” belongs. Further, the information processing apparatus 100 may calculate an individual score for the category “entertainment” using the content CT3 to which the category “entertainment” belongs. In this case, the information processing apparatus 100 may calculate the fake score of the content using the individual score corresponding to the category of the content.

  The method of learning (generating) the model in the above-described calculation of the individual score is not limited to the method described above, and any known technique can be applied. The generation of each model may be performed by appropriately using various conventional techniques related to machine learning. For example, the generation of the model may be performed using a technology related to machine learning of supervised learning such as SVM (Support Vector Machine). Further, for example, the generation of the model may be performed using a technology related to machine learning of unsupervised learning. For example, the generation of the model may be performed using a technique of deep learning (deep learning). For example, the model may be generated by appropriately using various deep learning techniques such as DNN (Deep Neural Network), RNN (Recurrent Neural Network), and CNN (Convolutional Neural Network). Note that the description regarding the generation of the model is an example, and the generation of the model may be performed by a learning method appropriately selected according to information that can be obtained.

[1-3. Content display)
Further, in the example of FIG. 1, a case where the information processing apparatus 100 provides one content CT11 to the terminal device 10 and the terminal device 10 displays the fake opinion information INF11 of the content CT11 including the fake score and the like together with the content CT11. Although shown, the display mode may be various modes. For example, the information processing apparatus 100 may provide the terminal device 10 with a list content in which a plurality of contents and fake opinion information of each content are displayed side by side.

  For example, the information processing apparatus 100 may provide the terminal device 10 with a list content in which a plurality of contents having similar contents and fake opinion information of each content are displayed side by side. For example, the information processing apparatus 100 may provide the terminal device 10 with a list content in which a plurality of contents distributed by similar providers (mediums) and fake opinion information of each content are displayed side by side. For example, based on various information stored in the storage unit 120 (see FIG. 3), the information processing apparatus 100 generates a list content in which a plurality of contents and fake opinion information of each content are displayed side by side. This will be described with reference to FIG. FIG. 11 is a diagram illustrating an example of display of fake opinion information according to the embodiment. The description of the same points as in FIG. 1 will be omitted as appropriate.

  In the example of FIG. 11, the information processing apparatus 100 provides the terminal device 10 with a list content in which the content CT51, the content CT52, and the content CT53 are vertically displayed in a list. Further, the information processing apparatus 100 transmits, to the terminal device 10, list contents arranged near the content corresponding to the fake opinion information INF51 of the content CT51, the fake opinion information INF52 of the content CT52, and the fake opinion information INF53 of the content CT53. The case of providing to

  As shown in FIG. 11, the terminal device 10 lists content CT51 whose information source is XX newspaper, content CT52 whose information source is YY newspaper, and content CT53 whose information source is ZZ newspaper. indicate. In addition, the terminal device 10 displays fake opinion information INF51 of the content CT51 near the content CT51. Specifically, the terminal device 10 displays the opinion information INF51 indicating that the fake score of the content CT51 is “15” and the fake degree is “high” below the content CT51.

  In addition, the terminal device 10 displays fake opinion information INF52 of the content CT52 near the content CT52. Specifically, the terminal device 10 displays the opinion information INF52 indicating that the fake score of the content CT52 is “0.5” and the fake degree is “low” below the content CT52. Further, the terminal device 10 displays fake opinion information INF53 of the content CT53 near the content CT53. Specifically, the terminal device 10 displays the opinion information INF53 indicating that the fake score of the content CT53 is “7” and the fake degree is “medium” below the content CT53. Thus, the user to whom the list content is provided from the information processing apparatus 100 can browse while comparing a plurality of contents. In this way, the user can browse the contents while comparing the contents while referring to the fake opinion information of the contents.

[1-4. Level judgment)
For example, the information processing apparatus 100 may determine the fake degree at a plurality of stages (levels) as described above using a plurality of thresholds. For example, the information processing apparatus 100 may determine the fake degree of the content using two thresholds, a first threshold and a second threshold.

  For example, when the fake score of the content is equal to or more than a first threshold (for example, “10”), the information processing apparatus 100 may determine that the fake degree of the content is “high”. For example, when the fake score is less than a first threshold (eg, “10”) and equal to or more than a second threshold (eg, “5”), the prediction device 100 determines that the fake degree of the content is “medium”. You may. For example, when the fake score is less than a second threshold (for example, “5” or the like), the prediction device 100 may determine that the fake degree of the content is “low”.

[1-5. Content change)
Note that the information processing apparatus 100 may provide various services using information collected in the determination regarding fake news. The information processing apparatus 100 may provide a service using information that guarantees the truth among the information collected in the determination regarding the fake news. The information processing apparatus 100 may be able to detect falsification of the content by appropriately using various conventional techniques. For example, the information processing device 100 may be able to detect falsification of the content by appropriately using various encryption techniques. For example, the information processing apparatus 100 may determine the authenticity of the content by confirming that the content has not been tampered with by appropriately using various encryption techniques.

  For example, the information processing apparatus 100 may be able to grasp the falsification of the content by using a technology related to a block chain. For example, the information processing apparatus 100 may make it possible to grasp the falsification of the content by treating one content as one block and linking the dependencies like a chain. For example, the information processing apparatus 100 may secure the information after certifying the authenticity by linking information that guarantees the authenticity with a blockchain. Also, for example, the information processing apparatus 100 may secure information by linking the information of falseness with a blockchain and proving falseness. For example, the information processing apparatus 100 may use various conventional techniques regarding hashes such as various hash functions. For example, the information processing apparatus 100 may use SHA (Secure Hash Algorithm) technology such as SHA-256 or SHA-512. Further, for example, the information processing apparatus 100 may use the technology of RIPEMD-160. The information processing apparatus 100 is not limited to the hash, and may use any technology as long as it can detect that the content has not been tampered with (changed). For example, the information processing apparatus 100 may use various conventional techniques related to elliptic curve encryption such as elliptic curve DSA (Digital Signature Algorithm).

  For example, the information processing apparatus 100 may make it possible to grasp the falsification of the contents by linking the citation relationships between the contents as a chain with each content as one block. For example, the information processing apparatus 100 uses a cryptographic information (for example, a hash value) generated based on a content (origin content) that is a source of a certain content to connect a citation relationship between the content like a chain. Thus, it may be possible to grasp the falsification of the content.

  For example, when there is a content (first cited content) that cites the original content, the information processing apparatus 100 may generate cryptographic information (first cipher information) generated based on the first cited content. For example, the information processing apparatus 100 may generate block data (first cited block data) corresponding to the first cited content based on the original cipher information and the first cited cipher information.

  Further, for example, when there is a content (second cited content) that cites the first cited content, the information processing apparatus 100 may generate the cryptographic information (second cipher information) based on the second cited content. . For example, the information processing apparatus 100 may generate block data (second cited block data) corresponding to the second cited content based on the first cipher information and the second cipher information. As described above, the information processing apparatus 100 may generate information (block chain information) in which blocks of content (block data) are linked based on a citation relationship between contents.

  In this case, for example, the information processing apparatus 100 may determine whether or not it is fake news by using a technology related to a blockchain. For example, in the case where certain origin content is not fake news (for example, fact), the information processing apparatus 100 has tampered with each block (quoted block) connected by a chain (genuine chain) starting from the origin content. May be determined (whether it is not fake news). For example, if it is verified in the genuine chain that the content (target content) has not been tampered with from the source content to the origin content, the information processing apparatus 100 may determine that the target content is not fake news. Good.

  For example, when a certain origin content is fake news, the information processing apparatus 100 determines whether each block (quoted block) connected by a chain (fake chain) starting from the origin content has not been changed. Is also good. For example, the information processing apparatus 100 determines that the target content is fake news when it is verified that the content (target content) has not been changed from the source content to the original content in the fake chain. Is also good.

  Thereby, the information processing apparatus 100 can suppress the possibility of the content being falsified while guaranteeing the content. The information processing device 100 can perform proof of truth or falsehood. Therefore, the information processing apparatus 100 can suppress the possibility that the falsified content is distributed. As described above, the information processing apparatus 100 can suppress the possibility that fake news is distributed.

[2. Configuration of information processing device]
Next, the configuration of the information processing apparatus 100 according to the embodiment will be described with reference to FIG. FIG. 3 is a diagram illustrating a configuration example of the information processing apparatus 100 according to the embodiment. As shown in FIG. 3, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130. The information processing apparatus 100 includes an input unit (for example, a keyboard and a mouse) for receiving various operations from an administrator or the like of the information processing apparatus 100, and a display unit (for example, a liquid crystal display) for displaying various information. May have.

(Communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 110 is connected to the network by wire or wirelessly, and transmits and receives information to and from the terminal device 10 and the provider device 20.

(Storage unit 120)
The storage unit 120 is realized by a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk. As illustrated in FIG. 3, the storage unit 120 according to the embodiment includes a provider information storage unit 121, a content information storage unit 122, an individual score information storage unit 123, a determination information storage unit 124, and true / false result information. And a storage unit 125.

(Provider information storage unit 121)
The provider information storage unit 121 according to the embodiment stores various information related to the provider of the content. FIG. 4 is a diagram illustrating an example of a provider information storage unit according to the embodiment. The provider information storage unit 121 illustrated in FIG. 4 includes items such as “provider ID”, “name”, “type”, and “credibility (fake rate)”.

  "Provider ID" indicates identification information for identifying the provider of the content. The content provider may be various providers such as newspaper publishers, magazine publishers, content providers, and individual users. “Name” indicates the name of the provider identified by the corresponding provider ID. FIG. 5 shows an example in which conceptual information such as “A medium” is stored in “Name”, but in actuality, a specific business name such as “XX Newspaper” may be used. . “Type” indicates the type of the provider identified by the corresponding provider ID. For example, the “type” stores information indicating whether the provider identified by the corresponding provider ID is an individual or an organization (corporation) or information indicating the type of medium. "Credit (fake rate)" indicates the credit of the provider identified by the corresponding provider ID. For example, “credibility (fake rate)” indicates a ratio of content corresponding to fake news among contents provided by the provider. For example, when the credit (fake rate) is “5”, it indicates that the probability that the content provided by the provider is fake news is 5%. In this case, the larger the value of the credit rating (fake rate) of the provider, the more the provider cannot be trusted.

  For example, in the example shown in FIG. 4, the provider (provider CP1) identified by the provider ID “CP1” indicates that the name is “A medium” and the type is “newspaper”. The provider CP1 indicates that the credit (fake rate) is “2” and the probability that the content provided by the provider CP1 is fake news is 2%.

  The provider information storage unit 121 is not limited to the above, and may store various types of information according to purposes. For example, the provider information storage unit 121 may store information on the business scale such as the location of the provider, the number of employees of the provider, and sales. For example, the provider information storage unit 121 may store information on the number of years since the provider started providing the content.

(Content information storage unit 122)
The content information storage unit 122 according to the embodiment stores various types of information related to content (article). FIG. 5 is a diagram illustrating an example of the content information storage unit according to the embodiment. The content information storage unit 122 shown in FIG. 5 has items such as “content ID”, “content information”, “provider ID”, “category”, “quoted content”, and “content”. Although not shown in FIG. 5, the content information storage unit 122 stores information on the date and time when each content was created.

  “Content ID” indicates identification information for identifying the content. “Content information” indicates the content identified by the corresponding content ID. In the example of FIG. 5, the content information is indicated by an abstract code such as “CDT11”, but each content information may include specific information of the content such as character information and image information included in the article. For example, as the content information, information corresponding to the content shown in parentheses such as “article A” and “article B” is stored. Further, for example, the “content information” stores a file path name indicating the storage location of the content.

  "Provider ID" indicates identification information for identifying the provider of the corresponding content. “Category” indicates classification information based on the content of the content. The “quoted content” indicates the content from which the corresponding content is generated. “Content” indicates the specific content of the information included in the corresponding content. For example, the information processing apparatus 100 extracts an important keyword (topic) from character information included in the content. Note that the information processing apparatus 100 may extract a topic from character information by appropriately using various conventional methods such as topic analysis (analysis). For example, the information processing apparatus 100 may extract a topic from the character information by appropriately analyzing the character information using a natural language processing technique such as morphological analysis. Further, for example, the information processing apparatus 100 may determine whether the content is positive or negative for the topic based on the syntactic relationship between the extracted topic and a keyword indicating topic affirmation or negation. . Then, the information processing apparatus 100 stores information indicating whether the content is positive or negative for the topic in the “content”.

  In the example of FIG. 5, the content identified by the content ID “CT11” (content CT11) indicates that the content is the article A provided by the providing source CP11. The content CT11 indicates that the content is classified into the category “politics”. The content CT11 indicates that there is no quoted content. The content CT11 indicates that the content is positive about the tax increase after the election. That is, the content CT11 indicates that the content is a news article about the tax increase after the election.

  The content information storage unit 122 is not limited to the above, and may store various types of information according to purposes. For example, the content information storage unit 122 may store information on the date and time when the content was acquired.

(Individual score information storage unit 123)
The individual score information storage unit 123 according to the embodiment stores individual score information on materials (elements) used for fake news determination. For example, the individual score information storage unit 123 stores individual score information regarding each determination element (determination element) used when determining whether or not the content is fake news. FIG. 6 is a diagram illustrating an example of an individual score information storage unit according to the embodiment. The individual score information storage unit 123 illustrated in FIG. 6 includes items such as “judgment element ID”, “judgment element”, and “individual score”.

  “Determination element ID” indicates identification information for identifying each determination element. The “judgment element” indicates the content of the judgment element identified by the corresponding judgment element ID. “Individual score” indicates an individual score of each determination element.

  In the example of FIG. 6, the judgment element (judgment element JE11) identified by the judgment element ID “JE11” indicates whether or not there is a content creation date. The judgment element JE11 indicates that a content without a creation date is assigned the individual score “0.2” as being likely to be fake news.

  The judgment element identified by the judgment element ID “JE12” (judgment element JE12) indicates whether or not evidence is quoted. The judgment element JE12 indicates that the content without the evidence citation is assigned the individual score “0.5”, assuming that the content may be fake news. The judgment element (judgment element JE13) identified by the judgment element ID “JE13” indicates whether or not there is a difference between the contents of the other provider and the contents. The determination element JE13 indicates that the content having a difference from the content of the other provider is assigned the individual score “7” as being likely to be fake news.

  The individual score information storage unit 123 is not limited to the above, and may store various individual score information according to the purpose.

(Determination information storage unit 124)
The determination information storage unit 124 according to the embodiment stores various types of information related to determining whether the content is fake news. FIG. 7 is a diagram illustrating an example of the determination information storage unit according to the embodiment. The determination information storage unit 124 illustrated in FIG. 7 has items such as “content ID”, “fake score”, and “determination information”.

  “Content ID” indicates identification information for identifying the content. “Fake score” indicates a fake score of the content identified by the corresponding content ID. The “fake score” stores a score indicating the degree of possibility that the corresponding content is fake news. “Judgment information” indicates whether or not the corresponding content is fake news.

  In the example of FIG. 7, the content identified by the content ID “CT11” (content CT11) indicates that the fake score is “15”. The content CT11 indicates that it is determined that the content may be fake news.

  The determination information storage unit 124 is not limited to the above, and may store various types of information according to purposes. For example, the determination information storage unit 124 may store information on the date and time when the score was calculated and the date and time when the determination was made.

(True / False Result Information Storage Unit 125)
The true / false result information storage unit 125 according to the embodiment stores various kinds of information regarding the true / false result of whether or not the content is fake news. For example, the true / false result information storage unit 125 stores various types of information regarding content for which it has been determined whether or not it was fake news among the content provided in the past. FIG. 8 is a diagram illustrating an example of the true / false result information storage unit according to the embodiment. The true / false result information storage unit 125 illustrated in FIG. 8 includes items such as “result ID”, “content ID”, “content information”, “providing source ID”, “category”, “quoted content”, and “determined fake result”. Having. Although not shown in FIG. 8, the true / false result information storage unit 125 stores information on the date and time when each content is created.

  “Result ID” indicates identification information for identifying a true / false result as to whether or not the content is fake news. “Content ID” indicates identification information for identifying the content. “Content information” indicates the content identified by the corresponding content ID. In the example of FIG. 8, the content information is indicated by an abstract code such as “CDT1”, but each content information may include specific information of the content such as character information and image information included in the article. For example, as the content information, information corresponding to the content shown in parentheses such as “article PA” and “article PB” is stored. Further, for example, the “content information” stores a file path name indicating the storage location of the content.

  "Provider ID" indicates identification information for identifying the provider of the corresponding content. “Category” indicates classification information based on the content of the content. The “quoted content” indicates the content from which the corresponding content is generated. “Confirmed fake result” indicates whether the corresponding content is fake news.

  In the example of FIG. 8, the true / false result identified by the result ID “RID1” indicates that the content (the content CT1) identified by the content ID “CT1” is the target. The content CT1 indicates an article PA provided by the provider CP1. The content CT1 indicates that the content is classified into the category “politics”. The content CT1 indicates that there is no quoted content. Further, the confirmed fake result of the content CT1 indicates a fake (erroneous information). That is, the content CT1 indicates that the content is erroneous information and corresponds to fake news.

  The true / false result information storage unit 125 is not limited to the above, and may store various types of information according to purposes. For example, the true / false result information storage unit 125 may store information on the date and time when true / false is determined.

(Control unit 130)
Returning to the description of FIG. 3, the control unit 130 is a controller, and is stored in a storage device inside the information processing apparatus 100 by, for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). Are realized by executing various programs (corresponding to an example of a distribution program) using the RAM as a work area. The control unit 130 is a controller, and is realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

  As illustrated in FIG. 3, the control unit 130 includes an acquisition unit 131, a calculation unit 132, a determination unit 133, a determination unit 134, and a provision unit 135, and functions and functions of information processing described below. Realize or execute. Note that the internal configuration of the control unit 130 is not limited to the configuration illustrated in FIG. 3, and may be another configuration as long as it performs information processing to be described later. Further, the connection relationship between the processing units included in the control unit 130 is not limited to the connection relationship shown in FIG. 3 and may be another connection relationship.

(Acquisition unit 131)
The acquisition unit 131 acquires various information. The acquisition unit 131 acquires various information from an external information processing device. The acquisition unit 131 acquires various information from the terminal device 10. The acquisition unit 131 acquires a content request from the terminal device 10. The acquisition unit 131 acquires various information from the provider device 20. The acquisition unit 131 acquires information about a provider from the provider device 20. The acquiring unit 131 acquires content-related information related to the content from the provider device 20. The acquisition unit 131 acquires various information from the storage unit 120. The acquisition unit 131 acquires various types of information from the provider information storage unit 121, the content information storage unit 122, the individual score information storage unit 123, the determination information storage unit 124, and the true / false result information storage unit 125.

  The acquisition unit 131 acquires content-related information related to content. The acquisition unit 131 acquires content-related information including information indicating content. The acquisition unit 131 acquires content-related information including information indicating a creation date of the content. The acquisition unit 131 acquires content-related information including information indicating whether there is evidence corresponding to the content indicated by the content. The acquisition unit 131 acquires content-related information including information indicating a provider of the content. The acquisition unit 131 acquires content-related information including information indicating the reliability of the content provider.

  The acquisition unit 131 acquires content related information including related content information that is information of related content having a predetermined relationship with the content. The acquisition unit 131 acquires content-related information including information indicating a provider of the related content. The acquisition unit 131 acquires content-related information including information indicating the reliability of the provider of the related content.

  In the example of FIG. 1, the acquisition unit 131 acquires the content CT11 of the provider CP11 from the provider device 20-1. The acquisition unit 131 acquires the content CT12 of the provider CP12 from the provider device 20-2. The acquisition unit 131 acquires the content CT13 of the provider CP13 from the provider device 20-3. The acquisition unit 131 acquires the content CT14 of the provider CP14 from the provider device 20-4.

(Calculation unit 132)
The calculation unit 132 calculates various information. The calculation unit 132 calculates various information based on the information stored in the storage unit 120. The calculation unit 132 calculates various information based on the information acquired by the acquisition unit 131. The calculation unit 132 calculates a score based on the information acquired by the acquisition unit 131. The calculating unit 132 calculates a score indicating the degree of possibility that the content is fake nice, based on the content-related information.

  In the example of FIG. 1, the calculation unit 132 calculates a score (fake score) of each content. For example, the calculation unit 132 calculates fake scores of the contents CT11 to CT14. The calculation unit 132 calculates a fake score of the contents CT11 to CT14 based on the information stored in the individual score information 123.

  For example, the calculation unit 132 calculates a score (fake score) using the above equation (1). The calculation unit 132 calculates a fake score of each content, as shown in the determination information storage unit 124 in FIG. The calculation unit 132 calculates a fake score of each content based on the above equation (1), content information of each content, and the like. The calculation unit 132 calculates the fake score of the content CT11 as “15”. The calculation unit 132 calculates the fake score of the content CT12 as “0.02”. The calculation unit 132 calculates the fake score of the content CT13 as “0.5”. The calculating unit 132 calculates the fake score of the content CT14 as “1”.

  The calculation unit 132 may generate (calculate) an individual score of the determination element. For example, the calculation unit 132 may derive (calculate) the individual score of each determination element using the information on the content stored in the truth result information storage unit 125 (see FIG. 8). In this case, the calculation unit 132 may have a function as a generation unit that generates information about an individual score. In addition, the information processing apparatus 100 may include a generation unit (not shown) that generates information on an individual score, such as the following model, separately from the calculation unit 132.

  For example, the calculation unit 132 may derive (calculate) each discriminant element as a feature (feature amount) and the weight of each discriminant element as an individual score. For example, the calculation unit 132 calculates an individual score by performing learning using the information of the content stored in the truth result information storage unit 125 as learning data (teacher data). For example, the calculation unit 132 generates a model by a learning process (model generation) using information of the content stored in the true / false result information storage unit 125, and thereby calculates a feature amount (determination element) in the model. The weight corresponding to each may be calculated as an individual score.

  For example, the calculation unit 132 may calculate the individual score for the judgment element by learning the weight (individual score) of each feature (judgment element) using the above equation (1).

  The calculation unit 132 may calculate the individual score information of each judgment element by learning the weight (individual score) of each feature (judgment element) using the content determined to be a fake as a positive example. For example, the calculation unit 132 may calculate individual score information of each determination element using the content CT1 determined as fake news in the truth result information storage unit 125 in FIG. 8 as a positive example. For example, when the content information CDT1 of the content CT1 is input, the calculation unit 132 performs the learning process such that the score output by the model outputs a score equal to or greater than a predetermined threshold (for example, “10”). . For example, when the content CT1 is the target, the calculation unit 132 performs the learning process so that the value (score) of “y” in the above equation (1) is equal to or larger than a determination threshold (for example, “10”). I do.

  Further, for example, the calculation unit 132 may calculate the individual score information of each determination element by taking the content CT2 determined as not fake news in the truth result information storage unit 125 in FIG. 8 as a negative example. . For example, when the content information CDT2 of the content CT2 is input, the calculation unit 132 performs the learning process such that the score output by the model becomes a score (for example, “0”) smaller than a predetermined threshold. . For example, when the content CT2 is a target, the calculation unit 132 sets the value (score) of “y” in the above equation (1) to a value smaller than the determination threshold (for example, “0”). Next, a learning process is performed.

  Further, for example, the calculation unit 132 may calculate the individual score information of each determination element by taking the content CT3 determined as not fake news in the truth result information storage unit 125 in FIG. 8 as a negative example. . For example, when the content information CDT3 of the content CT3 is input, the calculation unit 132 performs the learning process such that the score output by the model becomes a score smaller than a predetermined threshold (for example, “0”). . For example, when the content CT3 is targeted, the calculation unit 132 sets the value (score) of “y” in the above equation (1) to a value smaller than the determination threshold (for example, “0”). Next, a learning process is performed.

  For example, the calculation unit 132 may calculate an individual score for each content category. That is, the calculation unit 132 may generate a model for each content category. In the above example, the calculation unit 132 may calculate the individual score for the category “politics” using the contents CT1 and CT2 to which the category “politics” belongs. The calculating unit 132 may calculate the individual score for the category “entertainment” using the content CT3 to which the category “entertainment” belongs. In this case, the calculation unit 132 may calculate the fake score of the content using the individual score corresponding to the category of the content.

(Determining unit 133)
The determination unit 133 determines various information. The determination unit 133 determines various information based on the information stored in the storage unit 120. The determining unit 133 determines various information based on the information acquired by the acquiring unit 131. The determination unit 133 determines various information based on the information calculated by the calculation unit 132. The determining unit 133 determines whether the content is applicable to fake news based on the information acquired by the acquiring unit 131.

  The determining unit 133 determines whether or not the content satisfies a condition regarding fake nice, based on the content-related information acquired by the acquiring unit 131. The determination unit 133 determines whether the content satisfies the condition based on a comparison between the content indicated by the content and the content indicated by the related content. The determination unit 133 determines whether the content satisfies the condition based on a comparison between the content indicated by the content and the content indicated by the related content. The determination unit 133 determines whether the content satisfies the condition based on the score calculated by the calculation unit 132. The determining unit 133 determines whether the content satisfies the condition based on a comparison between the score calculated by the calculating unit 132 and a predetermined threshold.

  In the example of FIG. 1, the determination unit 133 determines whether a condition regarding fake nice is satisfied. For example, when one content satisfies a condition regarding fake nice, the determination unit 133 may determine that the one content is fake news (determines that there is a fake possibility. For example, the determination unit 133 determines If the content does not satisfy the condition regarding fake nice, it is determined that there is no possibility that the one content is fake news (no fake possibility).

  For example. When the fake score of the content is equal to or more than a predetermined threshold (threshold for determination), the determination unit 133 determines that the content has the possibility of fake. In the example of FIG. 1, when the fake score of the content is equal to or greater than the determination threshold “10”, the determination unit 133 determines that the content has the possibility of fake.

  For example, since the fake score “15” of the content CT11 is equal to or greater than the determination threshold “10”, the determination unit 133 determines that the content CT11 has the possibility of fake. In addition, since the fake score “0.02” of the content CT12 is less than the determination threshold “10”, the determination unit 133 determines that the content CT12 has no fake possibility. Since the fake score “0.5” of the content CT13 is less than the determination threshold “10”, the determination unit 133 determines that the content CT13 has no fake possibility. In addition, since the fake score “1” of the content CT14 is less than the determination threshold “10”, the determination unit 133 determines that the content CT14 has no fake possibility. Accordingly, the determination unit 133 determines that the content CT11 has the possibility of fake, and determines that the contents CT12 to CT14 are not possible.

(Determining unit 134)
The determining unit 134 determines various information. The determining unit 134 determines various information based on the information stored in the storage unit 120. The determining unit 134 determines various information based on the information acquired by the acquiring unit 131. The determination unit 134 determines various information based on the information calculated by the calculation unit 132. The determining unit 133 determines various information based on the information determined by the determining unit 133.

  In the example of FIG. 1, the determining unit 134 determines the content to be provided to the user U1 in response to a content request from the terminal device 10. The determination unit 134 determines the content to be provided to the user U1 by appropriately using various information, but the determination unit 134 determines the content CT11 to be the content to be provided to the user U1. For example, the determining unit 134 may determine the content to be provided to the user U1 based on the attribute information of the user U1. For example, when the user U1 is a user who is interested in politics, the determination unit 134 may determine the content belonging to the category “politics” as the content to be provided to the user U1. Further, the determination unit 134 may determine not to provide the content determined to have the possibility of fake by the determination unit 133. In this case, the determination unit 134 may determine the content to be provided to the user U1 other than the content CT11 determined to be fake by the determination unit 133.

(Provider 135)
The providing unit 135 provides various information. The providing unit 135 transmits various information to the terminal device 10. The providing unit 135 distributes various types of information to the terminal device 10. For example, the providing unit 135 distributes fake opinion information to the terminal device 10.

  The providing unit 135 is fake opinion information that is used as a material for determining whether the content is fake nice based on the determination by the determination unit 133, and is displayed together with the content on the terminal device 10 used by the user. Is provided to the terminal device 10. The providing unit 135 provides fake opinion information including the score calculated by the calculating unit 132.

  In FIG. 1, the providing unit 135 adds information to the content CT11 determined as the content to be provided to the user U1. For example, the providing unit 135 adds fake opinion information including a fake score “15” and information indicating that there is a possibility of fake to the information provided to the user U1. The providing unit 135 adds fake information as information to be provided to the user U1 together with the content information CDT11 (article A) of the content CT11, as shown in the providing content DC11.

  The providing unit 135 provides the terminal device 10 with the content CT11 and the fake score “15” and information indicating that there is a possibility of fake. The providing unit 135 transmits to the terminal device 10 the content CT11, the fake score “15”, and the fake opinion information INF11 indicating the possibility of fake.

[3. Information processing flow)
Next, a procedure of information processing by the information processing system 1 according to the embodiment will be described with reference to FIG. FIG. 9 is a flowchart illustrating an example of information processing according to the embodiment. Specifically, FIG. 9 is a flowchart illustrating an example of information processing regarding content determination.

  As shown in FIG. 9, the information processing apparatus 100 acquires content-related information related to content (step S101). For example, the information processing apparatus 100 acquires content-related information related to the content from the storage unit 120 (see FIG. 3).

  Further, the information processing apparatus 100 determines whether or not the content satisfies a condition regarding fake nice based on the content-related information (step S102). For example, the information processing apparatus 100 determines whether or not the content satisfies a condition regarding fake nice, based on the fake score of the content calculated using the above equation (1). For example, if the fake score of the content is equal to or greater than the determination threshold, the information processing apparatus 100 determines that the content has the possibility of fake. In the example of FIG. 1, when the fake score of the content is equal to or greater than the determination threshold “10”, the information processing apparatus 100 determines that the content has the possibility of fake.

  Next, a procedure of information processing by the information processing system 1 according to the embodiment will be described with reference to FIG. FIG. 10 is a flowchart illustrating an example of information processing according to the embodiment. Specifically, FIG. 10 is a flowchart illustrating an example of information processing regarding provision of content.

  As shown in FIG. 10, the information processing device 100 acquires a content request from the terminal device 10 (Step S201). Thereafter, the information processing apparatus 100 determines whether the content to be provided has a possibility of fake (step S202). For example, the information processing device 100 determines whether the content to be transmitted (distributed) to the terminal device 10 has the possibility of fake or not.

  Then, when the content to be provided has the possibility of fake (Step S202: Yes), the information processing apparatus 100 provides the fake opinion information together with the content (Step S203). For example, when the content to be provided has the possibility of fake, the information processing apparatus 100 transmits, to the terminal device, Provide to 10.

  On the other hand, when the content to be provided does not have the possibility of fake (step S202: No), the information processing apparatus 100 provides the content (step S204). For example, when the content to be provided does not have the possibility of fake, that is, when the content to be provided has no possibility of fake, the information processing apparatus 100 provides only the content to the terminal device 10. In addition, even if the content to be provided has no fake possibility, the information processing apparatus 100 transmits fake opinion information including the fake score of the content and information indicating that the content is not fake possible together with the content to the terminal. It may be provided to the device 10.

[4. effect〕
As described above, the information processing apparatus 100 according to the embodiment includes the obtaining unit 131, the determining unit 133, and the providing unit 135. The acquisition unit 131 acquires content-related information related to content. In addition, the determination unit 133 determines whether the content satisfies a condition regarding fake nice, based on the content-related information acquired by the acquisition unit 131. The providing unit 135 is fake opinion information that is used as a material for determining whether the content is fake nice based on the determination by the determination unit 133, and is displayed together with the content on the terminal device 10 used by the user. Is provided to the terminal device 10.

  As described above, the information processing apparatus 100 according to the embodiment determines whether the content satisfies the condition related to fake nice based on the content-related information, and determines whether the content corresponds to fake nice based on the determination. By providing the fake opinion information as a material to the terminal device 10, it is possible to provide appropriate information to the user.

  In addition, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires content-related information including information indicating content.

  As described above, the information processing apparatus 100 according to the embodiment obtains the content-related information including the information indicating the content, and can perform the determination in consideration of the information of the content itself, thereby providing appropriate information to the user. be able to.

  In the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires content-related information including information indicating a creation date of the content.

  As described above, the information processing apparatus 100 according to the embodiment can obtain the content related information including the information indicating the content creation date, and can determine the content in consideration of the content creation date. Information can be provided.

  Further, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires content-related information including presence / absence information of evidence corresponding to the content indicated by the content.

  As described above, the information processing apparatus 100 according to the embodiment obtains the content-related information including the presence / absence information of the evidence corresponding to the content indicated by the content. Providing appropriate information to

  In the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires content-related information including information indicating a provider of the content.

  As described above, the information processing apparatus 100 according to the embodiment acquires content-related information including information indicating the provider of the content, and can determine the content in consideration of the provision of the content. It can be carried out.

  In the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires content-related information including information indicating the reliability of the provider of the content.

  As described above, the information processing apparatus 100 according to the embodiment can obtain the content-related information including the information indicating the reliability of the content provider, and can determine the content in consideration of the reliability of the content provision. Providing appropriate information to

  In the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires content related information including related content information that is information of related content having a predetermined relationship with the content.

  As described above, since the information processing apparatus 100 according to the embodiment acquires the content related information including the related content information that is the information of the related content having the predetermined relationship with the content, the information processing apparatus 100 can perform the determination in consideration of the related content. Thus, appropriate information can be provided to the user.

  Further, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires content-related information including information indicating a provider of the related content.

  As described above, the information processing apparatus 100 according to the embodiment can obtain the content related information including the information indicating the provider of the related content, and can perform the determination in consideration of the provider of the related content. Information can be provided.

  In the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires content-related information including information indicating the reliability of the provider of the related content.

  As described above, the information processing apparatus 100 according to the embodiment can determine by taking into account the reliability of the provider of the related content by acquiring the content related information including the information indicating the reliability of the provider of the related content. Therefore, appropriate information can be provided to the user.

  In the information processing apparatus 100 according to the embodiment, the determination unit 133 determines whether the content satisfies the condition based on a comparison between the content indicated by the content and the content indicated by the related content.

  As described above, the information processing apparatus 100 according to the embodiment determines whether the content satisfies the condition based on the comparison between the content indicated by the content and the content indicated by the related content. Based on this, appropriate information can be provided to the user.

  In the information processing apparatus 100 according to the embodiment, the determination unit 133 determines whether the content satisfies the condition based on a comparison between the content indicated by the content and the content indicated by the related content.

  As described above, the information processing apparatus 100 according to the embodiment provides appropriate information to the user by determining whether the content satisfies the condition based on the comparison between the content indicated by the content and the content indicated by the related content. It can be performed.

  Further, the information processing apparatus 100 according to the embodiment includes a calculation unit 132. The calculating unit 132 calculates a score indicating the degree of possibility that the content is fake nice, based on the content-related information. The determination unit 133 determines whether the content satisfies the condition based on the score calculated by the calculation unit 132.

  As described above, the information processing apparatus 100 according to the embodiment provides appropriate information to the user by determining whether the content satisfies the condition based on the comparison between the content indicated by the content and the content indicated by the related content. It can be performed.

  In the information processing apparatus 100 according to the embodiment, the determination unit 133 determines whether the content satisfies the condition based on a comparison between the score calculated by the calculation unit 132 and a predetermined threshold.

  As described above, the information processing apparatus 100 according to the embodiment determines whether the content satisfies the condition based on the comparison between the score calculated by the calculation unit 132 and the predetermined threshold value, and Information can be provided.

  In the information processing apparatus 100 according to the embodiment, the providing unit 135 provides fake opinion information including the score calculated by the calculating unit 132.

  As described above, the information processing apparatus 100 according to the embodiment can provide appropriate information to the user by providing the fake view information including the score calculated by the calculation unit 132.

[5. Hardware configuration)
The information processing apparatus 100 according to the embodiment described above is realized by, for example, a computer 1000 having a configuration as shown in FIG. FIG. 12 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device. The computer 1000 has a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

  The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400, and controls each unit. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, a program that depends on hardware of the computer 1000, and the like.

  The HDD 1400 stores a program executed by the CPU 1100, data used by the program, and the like. The communication interface 1500 receives data from another device via the network N, sends the data to the CPU 1100, and transmits the data determined by the CPU 1100 to the other device via the network N.

  The CPU 1100 controls output devices such as a display and a printer and input devices such as a keyboard and a mouse via the input / output interface 1600. The CPU 1100 obtains data from an input device via the input / output interface 1600. Further, CPU 1100 outputs the determined data to an output device via input / output interface 1600.

  The media interface 1700 reads a program or data stored in the recording medium 1800 and provides the program or data to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc), a PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. And so on.

  For example, when the computer 1000 functions as the information processing apparatus 100 according to the embodiment, the CPU 1100 of the computer 1000 implements the function of the control unit 130 by executing a program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800. However, as another example, these programs may be obtained from another device via the network N.

  As described above, some of the embodiments and modifications of the present application have been described in detail with reference to the drawings. However, these are exemplifications, and various embodiments are described based on the knowledge of those skilled in the art, including the embodiments described in the lines of the disclosure. The present invention can be embodied in other forms in which modifications and improvements have been made.

[6. Others)
Further, among the processes described in the above embodiments and modifications, all or a part of the processes described as being performed automatically can be manually performed, or described as being performed manually. All or a part of the processing can be automatically performed by a known method. In addition, the processing procedures, specific names, and information including various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown.

  Each component of each device illustrated is a functional concept, and does not necessarily need to be physically configured as illustrated. That is, the specific form of distribution / integration of each device is not limited to the one shown in the figure, and all or a part thereof may be functionally or physically distributed / arbitrarily divided into arbitrary units according to various loads and usage conditions. Can be integrated and configured.

  Further, the above-described embodiments and modified examples can be appropriately combined within a range that does not contradict processing contents.

  Further, the “section (section, module, unit)” described above can be read as “means”, “circuit”, or the like. For example, the acquiring unit can be replaced with an acquiring unit or an acquiring circuit.

1 Information Processing System 100 Information Processing Device 121 Provider Information Storage Unit 122 Content Information Storage Unit 123 Individual Score Information Storage Unit 124 Judgment Information Storage Unit 125 True / False Result Information Storage Unit 130 Control Unit 131 Acquisition Unit 132 Calculation Unit 133 Judgment Unit 134 Determining unit 135 providing unit 10 terminal device N network

Claims (15)

An acquisition unit for acquiring content-related information related to the content,
Based on the content-related information acquired by the acquisition unit, a determination unit that determines whether the content satisfies a condition regarding fake nice,
Based on the determination by the determination unit, the fake opinion information serving as a material for determining whether the content corresponds to the fake nice, the fake opinion information displayed together with the content on a terminal device used by a user, A providing unit that provides the terminal device;
Equipped with a,
The acquisition unit,
An information processing apparatus , comprising: acquiring the content-related information including presence / absence information corresponding to the content indicated by the content . An acquisition unit for acquiring content-related information related to the content,
Based on the content-related information acquired by the acquisition unit, a determination unit that determines whether the content satisfies a condition regarding fake nice,
Based on the determination by the determination unit, the fake opinion information serving as a material for determining whether the content corresponds to the fake nice, the fake opinion information displayed together with the content on a terminal device used by a user, A providing unit that provides the terminal device;
With
The acquisition unit,
Acquiring the content related information including related content information that is information of related content having a predetermined relationship with the content,
The determination unit includes:
Based on a comparison of the contents and the content indicated by the content the indicated relationship content, information processing apparatus you characterized by determining the content whether the condition is satisfied. The acquisition unit,
The information processing apparatus according to claim 2 , wherein the content-related information including information indicating a provider of the related content is acquired. The acquisition unit,
The information processing apparatus according to claim 3 , wherein the content-related information including information indicating a reliability of a provider of the related content is acquired. The acquisition unit,
The information processing apparatus according to any one of claims 1 to 4, wherein the content-related information including information indicating the content is acquired. The acquisition unit,
The information processing apparatus according to claim 5 , wherein the content-related information including information indicating a creation date of the content is acquired. The acquisition unit,
The information processing apparatus according to any one of claims 1 to 6 , wherein the content-related information including information indicating a provider of the content is acquired. The acquisition unit,
The information processing apparatus according to claim 7 , wherein the content-related information including information indicating a reliability of a provider of the content is acquired. Based on the content-related information, a calculating unit that calculates a score indicating the degree of possibility that the content is the fake nice,
Further comprising
The determination unit includes:
On the basis of the score calculated by the calculation unit, the information processing apparatus according to any one of claims 1 to 8, wherein the content is equal to or determining whether the condition is satisfied. The determination unit includes:
The information processing apparatus according to claim 9 , wherein it is determined whether the content satisfies the condition based on a comparison between the score calculated by the calculation unit and a predetermined threshold. The providing unit,
The information processing apparatus according to claim 9 or claim 10, characterized in that providing the fake view information including the score calculated by the calculation unit. An information processing method executed by a computer,
An acquisition step of acquiring content-related information related to the content;
Based on the content-related information acquired by the acquiring step, a determining step of determining whether the content satisfies a condition regarding fake nice,
Based on the determination in the determination step, the content is fake opinion information that serves as a material for determining whether the content corresponds to the fake nice, the fake opinion information displayed along with the content on a terminal device used by the user, Providing step for providing to the terminal device;
Only including,
The obtaining step includes:
An information processing method , comprising: acquiring the content-related information including information indicating whether there is evidence corresponding to the content indicated by the content . An acquisition procedure for acquiring content-related information related to the content;
Based on the content-related information obtained by the obtaining step, a determining step of determining whether the content satisfies a condition related to fake nice,
Based on the determination by the determination procedure, the fake opinion information serving as a material for determining whether the content falls under the fake nice, the fake opinion information displayed together with the content on a terminal device used by a user, Providing procedure to be provided to the terminal device;
To the computer ,
The acquisition procedure includes:
An information processing program for acquiring the content-related information including presence / absence information of evidence corresponding to the content indicated by the content . An information processing method executed by a computer,
An acquisition step of acquiring content-related information related to the content;
A determination step of determining whether the content satisfies a condition regarding fake nice, based on the content-related information acquired by the acquisition step,
Based on the determination by the determination step, the content is fake opinion information that serves as a material for determining whether the content corresponds to the fake nice, and the fake opinion information displayed together with the content on a terminal device used by a user is the Providing step for providing to the terminal device;
Including
The obtaining step includes:
Acquiring the content related information including related content information that is information of related content having a predetermined relationship with the content,
The determining step includes:
Determining whether the content satisfies the condition based on a comparison between the content indicated by the content and the content indicated by the related content
An information processing method, comprising: An acquisition procedure for acquiring content-related information related to the content;
Based on the content-related information acquired by the acquisition procedure, a determination procedure of determining whether the content satisfies a condition regarding fake nice,
Based on the determination by the determination procedure, the content is fake opinion information serving as a material for determining whether the content corresponds to the fake nice, the fake opinion information displayed together with the content on a terminal device used by the user, Providing procedure to be provided to the terminal device;
To the computer,
The acquisition procedure includes:
Acquiring the content related information including related content information that is information of related content having a predetermined relationship with the content,
The determination procedure includes:
Determining whether the content satisfies the condition based on a comparison between the content indicated by the content and the content indicated by the related content
An information processing program characterized by the following.

Images