JP2024042574A - Information processing device, information processing method, and information processing program - Google Patents

Abstract

To appropriately estimate whether content satisfies evaluation conditions.SOLUTION: An information processing device according to the present application comprises an acquisition unit and an estimation unit. The acquisition unit acquires action information of a target user, who is a user who took a prescribed action at a time point before first content satisfies evaluation conditions, the evaluation conditions being conditions on content evaluation. The estimation unit estimates whether second content, which does not satisfy evaluation conditions at a time point of processing and for which a target user took a prescribed action, satisfies evaluation conditions after the time point of processing on the basis of the action information of the target user.SELECTED DRAWING: Figure 3

Description

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

Conventionally, techniques have been provided for estimating how various offerings such as content will be evaluated in the future. For example, technology has been provided that implements a marketing research method for predicting the hit of a new product.

Japanese Patent Application Publication No. 2007-272571

However, the above-mentioned conventional technology has room for improvement. The above conventional technology predicts whether a new product will be a hit or not, and it is difficult to apply it to products other than new products.For example, it is difficult to apply it to products other than new products. It is difficult to apply this to content that is provided sequentially. Therefore, it is desired to appropriately estimate whether content satisfies evaluation conditions.

The present application has been made in view of the above, and aims to provide an information processing device, an information processing method, and an information processing program that appropriately estimate whether content satisfies evaluation conditions.

The information processing device according to the present application is a user who has performed a predetermined action on a first content that satisfies an evaluation condition that is a condition regarding evaluation of content at a time before the first content satisfies the evaluation condition. an acquisition unit that acquires user behavior information; and a content that the target user has performed the predetermined behavior based on the behavior information of the target user, and that does not satisfy the evaluation condition at the time of processing. The present invention is characterized by comprising an estimation unit that estimates whether a certain second content satisfies the evaluation condition after the time of the processing.

According to one aspect of the embodiment, it is possible to appropriately estimate whether the content satisfies the evaluation conditions.

FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of an information processing system according to an embodiment. FIG. 3 is a diagram illustrating a configuration example of an information processing device according to an embodiment. FIG. 4 is a diagram illustrating an example of a user information storage unit according to the embodiment. FIG. 5 is a diagram illustrating an example of a content information storage unit according to the embodiment. FIG. 6 is a diagram illustrating an example of an action history information storage unit according to the embodiment. FIG. 7 is a diagram illustrating an example of an innovator level information storage unit according to the embodiment. FIG. 8 is a flowchart illustrating an example of information processing according to the embodiment. FIG. 9 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing device.

DESCRIPTION OF THE PREFERRED EMBODIMENTS An information processing apparatus, an information processing method, and an embodiment of an information processing program (hereinafter referred to as "embodiments") according to the present application will be described in detail below with reference to the drawings. Note that the information processing apparatus, information processing method, and information processing program according to the present application are not limited to this embodiment. Further, in each of the embodiments below, the same parts are given the same reference numerals, and redundant explanations will be omitted.

(Embodiment)
[1. Information processing〕
An example of information processing according to the embodiment will be described using FIG. 1. FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. In FIG. 1, the information processing device 100 extracts a user who has performed a predetermined action from among a plurality of users as an innovator, and estimates whether the content satisfies the conditions regarding evaluation based on the action of the user extracted as an innovator. is shown as an example. In addition, although comics will be explained below as an example of content, video content such as a drama may also be used. That is, the content may be any type of content as long as it can be processed. For example, the information processing device 100 provides information that is divided into a plurality of work groups, such as manga (comics) that is divided into a plurality of volumes and provided, or a drama that is divided and provided into a plurality of stories (episodes). Perform the following processing on the content.

[1-1. Information processing system configuration]
First, before describing an example of information processing, an example of the device configuration of the information processing system 1 will be described with reference to FIG. FIG. 2 is a diagram illustrating a configuration example of an information processing system according to an embodiment. As shown in FIG. 2, the information processing system 1 includes an information processing device 100, a service providing device 20, and a user terminal 10. For example, the information processing system 1 includes the number of user terminals 10 corresponding to the number of users. For example, when the number of users is 10,000, the information processing system 1 may include 10,000 user terminals 10. Each user terminal 10, service providing device 20, and information processing device 100 are connected via a predetermined network N so as to be communicable by wire or wirelessly. Note that the information processing system 1 shown in FIG. 2 may include multiple service providing devices 20 and multiple information processing devices 100.

The information processing device 100 is a computer that estimates the future potential of content based on user behavior. The information processing apparatus 100 executes processing using user behavior information regarding content (also referred to as "first content") that satisfies conditions regarding content evaluation (also referred to as "evaluation conditions"). In the following, winning a content-related award will be explained as an example of the evaluation condition, but the evaluation condition is not limited to receiving an award, and any other condition can be set. For example, the evaluation condition may be a condition regarding sales, such as reaching sales exceeding a predetermined value, or a condition regarding user posting, such as posting by the user a predetermined number of times or more.

The information processing device 100 executes a process using behavior information of a user who is an innovator, with a user (also referred to as a "target user") who performed a predetermined behavior before the first content satisfies the evaluation condition as an innovator. do. Although purchasing the content will be described below as an example of the predetermined action, the predetermined action is not limited to purchasing the content, and may be any action of the user. For example, the predetermined action may be a post indicating that the user highly rates the content, viewing the content by the user, renting the content by the user, or the like. In addition, the purchase of content by the user here may be the purchase of a physical book (book) on which the content is printed, a storage medium (DVD, etc.) on which the content is stored, or the purchase of an electronic version of the content. It may be in any manner such as purchasing content information (data) such as data (electronic files).

The information processing device 100 uses behavioral information of a user who is an innovator to determine whether content that does not satisfy the evaluation conditions at the time of processing (also referred to as "second content") satisfies the evaluation conditions after the time of processing. Estimate. The information processing device 100 receives various information from the user terminal 10. The information processing device 100 acquires user behavior information and the like from the user terminal 10. For example, the information processing device 100 acquires user behavior information at a predetermined timing. The information processing device 100 acquires a user's action history regarding content from the user terminal 10. The information processing device 100 acquires the user's behavior history including the content purchase history from the user terminal 10 . Note that the information processing device 100 may acquire the user's action history regarding the content from the service providing device 20.

The information processing device 100 receives various information from the service providing device 20. The information processing device 100 acquires information collected by the service providing device 20 through the content providing service from the service providing device 20. For example, the information processing device 100 requests information from the service providing device 20 and receives the requested information from the service providing device 20.

Note that the information processing device 100 may acquire information regarding the content providing service used by the user from the user terminal 10. Further, although FIG. 2 shows a case where the service providing device 20 that provides the content providing service and the information processing device 100 are separate, the information processing device 100 and the service providing device 20 may be integrated. good. In this case, the information processing device 100 provides a content providing service to the user.

The user terminal 10 is an information processing device used by a user. The user terminal 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. Note that below, the user terminal 10 may be referred to as a user. That is, in the following, the user can also be read as the user terminal 10.

The user terminal 10 is a computer that performs various processes in response to user operations. By operating the user terminal 10, the user performs various actions such as purchasing various contents and viewing various contents. The user terminal 10 displays various information using a display application or the like. For example, the user terminal 10 displays content. For example, the user terminal 10 displays content provided by the information processing device 100. The user terminal 10 executes processing for a user to purchase desired content using a shopping app or the like.

Further, the user terminal 10 transmits various information to the information processing device 100. For example, the user terminal 10 transmits behavior information and the like to the information processing device 100. For example, the user terminal 10 transmits, to the information processing apparatus 100, an action history including various information regarding content performed by the user.

[1-2. Information processing example]
The information processing example shown in FIG. 1 will now be described. In FIG. 1, a case will be described as an example in which the information processing apparatus 100 performs processing on a user group UG1 including a plurality of users such as users U1 to U5. As described above, in the example of FIG. 1, purchasing content will be described as an example of a predetermined action.

First, the information processing apparatus 100 extracts, as innovators, users who have purchased the first content that satisfies the evaluation condition from among the plurality of users before the first content satisfies the evaluation condition. (Step S11). In FIG. 1, the information processing device 100 extracts users who correspond to innovators from the user group UG1 using the behavior information (behavior history) of each of a plurality of users such as users U1 to U5 included in the user group UG1. . For example, the information processing apparatus 100 extracts, as the first content, content to which a tag indicating that the content corresponds to the first content is added, from among the plurality of contents.

The information processing device 100 selects an innovator who has purchased the first content before the first content satisfies the evaluation condition among the user group UG1 including a plurality of users such as users U1 to U5. Users who satisfy condition CD1 are extracted as innovators. The time before the content satisfies the evaluation conditions may be, for example, within 30 days after the content is released. For example, the information processing device 100 extracts a user who purchased the comic B2 before time TM1 when the first content, content CT31 (comic B2), won an award, as an innovator who satisfies the innovator condition CD1. In this case, the information processing device 100 uses the behavior history of each user included in the user group UG1 to select users who had purchased the manga B2 before the time TM1 when the manga B2 won the award from the user group UG1. Extract as an innovator from.

Furthermore, the information processing device 100 extracts users who purchased the comic B5 before the time TM2 when the first content, the content CT51 (comic B5), won an award, as innovators who satisfy the innovator condition CD1. In this case, the information processing device 100 uses the behavior history of each user included in the user group UG1 to select the users who purchased the manga B5 before the time TM2 when the manga B5 won the award from the user group UG1. Extract as an innovator from. Furthermore, the information processing apparatus 100 similarly extracts other first contents other than the contents CT31 and CT51 as innovators from the user group UG1. In FIG. 1, the information processing apparatus 100 extracts an innovator group UG1 including users U1, U3, U5, etc. from the user group UG1 as innovators who satisfy the innovator condition CD1. Note that, for the sake of explanation, FIG. 1 shows a case where a user who has purchased at least one piece of the first content before satisfying the evaluation condition is extracted as an innovator; however, the information processing device 100 Users who have purchased a predetermined number (for example, two or five) or more of the first content may be extracted as innovators.

Then, the information processing device 100 calculates the reliability (also referred to as "innovator degree") indicating the degree of power as an innovator for each user included in the innovator group UG1 (step S12). First, the information processing device 100 determines the ranking of each user included in the innovator group UG1. The information processing device 100 assigns a higher ranking to each user included in the innovator group UG1, the more first content the user has purchased before satisfying the evaluation condition. In FIG. 1, the information processing apparatus 100 determines the user U5 as the first, the user U1 as the second, and the user U3 as the third, as shown in the innovator information list IV1. Note that the above-described ranking determination is only an example, and the information processing apparatus 100 may determine the ranking of each user using arbitrary information. For example, the information processing device 100 may assign a higher ranking to the first content the earlier the predetermined action is taken.

Then, the information processing device 100 calculates the innovator degree of each user based on the ranking determined for each user included in the innovator group UG1. In FIG. 1, the information processing device 100 calculates the innovator level of the user U5 as "SC5", the innovator level of the user U1 as "SC1", and the innovator level of the user U3 as "SC3", as shown in the innovator information list IV1. do. For example, the information processing device 100 calculates the reciprocal of each user's rank as the innovator level of that user. In this case, the information processing device 100 sets the innovator level of the user U5 to "1 (=1/1)", the innovator level of the user U1 to "0.5 (=1/2)", and the innovator level of the user U3 to "1 (=1/1)". 0.33...(=1/3)". Note that the above-described determination of the ranking is only an example, and the information processing device 100 may calculate the innovator level of each user using arbitrary information.

Then, the information processing device 100 calculates a score regarding the evaluation for the second content that does not satisfy the evaluation conditions at that time (step S13). For example, the information processing device 100 replaces a content that does not satisfy the evaluation conditions at that time and whose latest volume is within n volumes (for example, 10 volumes) that is being provided (sold) at that time with the second content. You can also extract it by The information processing device 100 then calculates a score for the extracted second content. In FIG. 1, the information processing device 100 calculates scores related to evaluation for content CT11 (comic B1), content CT91 (comic B9), etc. included in the second content group SG1.

In FIG. 1, the information processing device 100 calculates the score of the comic B1, which is the second content, as "VL11" and the score of the comic B9, which is the second content, as "VL91", as shown in the second content information list RS1. do. For example, the information processing device 100 calculates a score for each second content based on the innovator degree of an innovator who has performed a predetermined action with respect to the second content. For example, the information processing device 100 calculates the score of each second content by summing up the innovator degrees of innovators who have performed a predetermined action with respect to the second content. In this case, the information processing device 100 calculates the total value of the innovator degrees of the innovators who purchased the comic B1 at the time of processing as the score of the comic B1. Note that the score calculation described above is only an example, and the information processing apparatus 100 may calculate the score of each content using arbitrary information.

Then, the information processing device 100 estimates whether the second content satisfies the evaluation condition after the time of processing (step S14). The information processing device 100 estimates whether the second content satisfies the evaluation condition based on a comparison between the score of the second content and a threshold related to evaluation. For example, if the score of the second content is equal to or greater than the threshold, the information processing device 100 estimates that the second content is likely to win an award in the future.

In FIG. 1, the information processing device 100 estimates whether the comic B1 satisfies the evaluation condition, as shown in the second content information list RS1. Since the score "VL11" of the comic B1 is greater than or equal to the threshold, the information processing device 100 estimates that the comic B1 will satisfy the evaluation condition in the future. That is, since the score "VL11" of the comic B1 is greater than or equal to the threshold, the information processing device 100 estimates that the comic B1 is likely to win an award in the future. Furthermore, the information processing device 100 estimates whether the comic B9 satisfies the evaluation conditions. Since the score “VL91” of the comic B9 is less than the threshold, the information processing device 100 estimates that the comic B9 will not satisfy the evaluation condition in the future. That is, since the score "VL91" of the comic B9 is less than the threshold, the information processing device 100 estimates that the comic B9 is unlikely to win an award in the future.

Further, the information processing apparatus 100 may determine the order of the second content in descending order of the score. In FIG. 1, the information processing apparatus 100 may determine the ranking of the comic B1 to be the first comic B1 when the score "VL11" is the highest. In this case, the information processing device 100 may estimate that a predetermined number (for example, 10) of second contents from the top satisfy the evaluation condition.

Further, the information processing apparatus 100 may generate a second content list in which the second content is sorted in descending order of score. The information processing device 100 may provide the generated second content list. For example, the information processing device 100 may provide the generated second content list to a content provider (also referred to as a "provider") such as a publisher or a distribution company. The information processing device 100 may transmit the generated second content list to a device (provider device) such as a PC or a smartphone used by the provider. In addition, the information processing device 100 provides a content list (also referred to as a "promising content list") in which only content estimated to satisfy the evaluation condition is extracted from the second content list as a list indicating content with high future potential. It may be provided to the original person. The information processing device 100 may transmit the promising content list to a device (provider device) such as a PC or a smartphone used by the provider. Note that the processing described above is only an example, and the information processing apparatus 100 may perform processing using various types of information.

As described above, the information processing apparatus 100 can appropriately estimate whether the content satisfies the evaluation conditions by estimating the future evaluation of the content based on the information of the innovators among the user group. In this manner, the information processing apparatus 100 extracts as innovators users who performed a predetermined action before the condition was met with respect to the condition-matching content that is the first content that matched the condition. Then, the information processing device 100 extracts content in which the extracted innovator has performed a predetermined action as second content, and estimates whether the second content can become condition-matching content in the future based on the action by the innovator. do.

For example, the information processing device 100 executes processing on content such as manga (comics) or dramas, which are continuously provided as a series of works. For example, the information processing device 100 executes processing on evaluation conditions such as winning an award, exceeding a predetermined value in sales, or exceeding a predetermined number of posts on a social networking service (SNS) (going viral). The SNS referred to here may be any SNS as long as the user can post input information, and may be any SNS such as Twitter (registered trademark), Facebook (registered trademark), or Instagram (registered trademark).

For example, the information processing device 100 extracts a user who purchased the content before the condition was met as an innovator, and based on the purchase history of the innovator, the more content the innovator purchased before the condition was met, the higher the reliability of the innovator (innovator level). ) is estimated to be high. Note that innovators may be extracted for each category of content, and the degree of innovator for each category may be calculated for the innovators extracted for each category. Further, the information processing device 100 may extract content for which the number of innovators who have purchased the content is equal to or greater than a predetermined number and does not satisfy the evaluation condition at the time of processing. The information processing apparatus 100 may provide information on the extracted content as content that is likely to meet the conditions in the future.

[1-2-1. Innovator power]
Note that the reliability level (degree of innovator) indicating the above-mentioned innovator power is only one example, and the information processing device 100 may calculate the innovator power (degree of innovator) using various information. For example, the information processing device 100 may calculate the innovator degree based on what kind of person (user) performed what action (behavior) at what time. For example, the information processing apparatus 100 may calculate the innovator level based on the time axis corresponding to the point in time, the action for the relevant title, and what kind of person the person is (trustworthiness of the person).

For example, the information processing device 100 may extract users (innovators) on a time axis, and calculate the degree of innovator based on their actions and reliability. For example, the time axis includes before winning an award such as the Manga Award, before a hit indicated by a hit label attached according to a predetermined logic, before becoming a buzz on SNS or search, before being announced as a media, etc.

In addition, actions for the relevant title include multiple purchases, continuous purchases such as volumes 1 and 2, reviews, presence or absence of reviews, good (positive) evaluations in reviews, good (positive) comments in reviews, continuing reviews, and dissemination on SNS. etc. are included.

In addition, a person's credibility is determined by their knowledge, the amount of manga they have read, the genres they have read, evaluations by others, number of followers, number of good reviews such as likes, freshness, etc. Includes early action, amount, more action, etc.

Further, the information processing device 100 may change the coefficient of innovator power for each category. For example, the information processing device 100 may increase the innovator power coefficient corresponding to boys' comics for an innovator who is strong in boys' comics. Furthermore, the information processing device 100 may increase the innovator power coefficient as the amount of manga that a person has read so far (the deeper the person's knowledge). Furthermore, the information processing device 100 may increase the coefficient of innovator power for those who bought the product earlier, considering that the product is fresher. Further, the information processing device 100 may increase the coefficient of innovator power, assuming that the more followers a person has on SNS, the higher the person's ability to communicate and the higher the reliability from others. For example, the information processing device 100 may increase the innovator power coefficient depending on the number of followers of the person who posted the review and the number of likes (good evaluations) for the review.

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

(Communication Department 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card). The communication unit 110 is connected to a network (for example, network N in FIG. 2) by wire or wirelessly, and transmits and receives information to and from the user terminal 10.

(Storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 3, the storage unit 120 according to the embodiment includes a user information storage unit 121, a content information storage unit 122, an action history information storage unit 123, and an innovator level information storage unit 124. Note that the storage unit 120 stores various information in addition to the above. The storage unit 120 stores various information used for processing, such as threshold values.

(User information storage unit 121)
The user information storage unit 121 according to the embodiment stores various information regarding users. For example, the user information storage unit 121 stores various information regarding user attributes and various information regarding user behavior. FIG. 4 is a diagram illustrating an example of a user information storage unit according to the embodiment. The user information storage unit 121 shown in FIG. 4 includes items such as "user ID", "age", "gender", "home", "place of work", and "type".

"User ID" indicates identification information for identifying a user. Moreover, "age" indicates the age of the user identified by the user ID. Note that the "age" may be a specific age of the user identified by the user ID, such as 35 years old. Furthermore, “gender” indicates the gender of the user identified by the user ID.

"Home" indicates the location information of the user's home identified by the user ID. In the example shown in FIG. 4, "Home" is illustrated as an abstract code such as "LC1-1," but it may also be information indicating latitude and longitude. For example, "Home" may also be the name of a region or an address.

Further, "work location" indicates location information of the work location of the user identified by the user ID. In the example shown in FIG. 4, the "work location" is illustrated as an abstract code such as "LC1-2", but it may also be information indicating latitude or longitude. Further, for example, the "work location" may be a region name or address.

Further, "type" indicates the type of user identified by the user ID. For example, "type" indicates whether the user identified by the user ID corresponds to an innovator. Note that in the example shown in FIG. 4, a case is illustrated in which only two types of "type" are classified, ie, innovator (user) and general (user), but there may be three or more types. For example, the "type" may be one of five types based on the innovator theory: innovator, early adopter, early majority, late majority, and laggard.

For example, in the example of FIG. 4, the age of the user identified by the user ID "U1" is "20s" and the gender is "male." Also, for example, the user identified by the user ID "U1" indicates that the home address is "LC1-1." Also, for example, the user identified by the user ID "U1" indicates that the workplace is "LC1-2." Also, for example, the user identified by the user ID "U1" indicates that the user corresponds to the type "innovator."

Note that the user information storage unit 121 is not limited to the above, and may store various information depending on the purpose. For example, the user information storage unit 121 may store other demographic attribute information and psychographic attribute information. For example, the user information storage unit 121 may store information such as name, family structure, income, interests, lifestyle, and the like. Further, the user information storage unit 121 may store information (terminal ID) that identifies the user terminal 10 used by the user.

(Content information storage unit 122)
The content information storage unit 122 according to the embodiment stores various information regarding content. FIG. 5 is a diagram illustrating an example of a 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", "category", and "posted information". "Posted information" includes items such as "comment", "user", "good", and "bad".

"Content ID" indicates identification information for identifying content. "Content" indicates the name of the content identified by the content ID. "Content" indicates content that is divided into multiple work groups and provided. In FIG. 5, "content" is shown in an abstract manner such as "comic B1", but it is assumed that it is a specific name such as the title of the content. Further, "category" indicates classification information based on the contents of the content.

The "latest number" indicates the latest number that was last provided for the content. For example, when the content category is "manga", the latest number indicates the number of volumes (latest volume number) of the manga that was last provided. Further, when the content category is "drama", the latest number indicates the number of episodes (latest episode number) that were last provided for the drama.

“Condition achievement” indicates whether or not the content has satisfied the evaluation conditions at that time. Moreover, "score" indicates a score related to the evaluation calculated for the content. In addition, in the example of FIG. 6, although the score is abstractly shown as "VL1" etc., the score is a concrete numerical value. Further, if the score is "-" (hyphen), it indicates that the score of the content has not yet been calculated. For example, content for which evaluation conditions have been achieved may not be subject to score calculation.

Further, "comment" indicates a comment (user input information) posted in the corresponding post. Moreover, "user" indicates the user who posted the corresponding comment. For example, "user" stores the identification information (user ID) of the user who posted the corresponding comment. Furthermore, "good" indicates the number of times good (positive) evaluations have been posted for the corresponding comment. Moreover, "bad" indicates the number of times bad (negative) evaluations have been posted for the corresponding comment.

In the example of FIG. 5, the comic B1 (content CT11) identified by the content ID "CT11" indicates that it is a content of the category "comic". Manga B1 indicates that up to 10 volumes have been provided. Further, the comic B1 indicates that the evaluation conditions have not been achieved at that time. Further, the comic B1 indicates that the score regarding evaluation is "VL1".

It also shows that comment CM1 has been posted regarding content CT11. Further, for example, the user who posted the comment CM1 is the user (user U1) identified by the user ID "U1". For example, comment CM1 is text information that refers to comic B1 posted by user U1. Further, regarding comment CM1, the number of times it has been evaluated as "good" is "200" times, and the number of times it has been evaluated as "bad" is "10" times.

Further, in the example of FIG. 5, the television drama D1 (content CT21) identified by the content ID "CT21" indicates that it is a content of the category "TV drama". The TV drama D1 indicates that up to five episodes are provided. Furthermore, the TV drama D1 indicates that the evaluation conditions have been achieved at that point. Furthermore, since the television drama D1 has already achieved the conditions regarding evaluation and is not subject to score calculation, it indicates that the score regarding evaluation has not yet been calculated.

Note that the content information storage unit 122 is not limited to the above, and may store various information depending on the purpose. For example, the content information storage unit 122 may store information regarding the date and time when the content was acquired and the date and time when the content was created. The content information storage unit 122 may store information regarding evaluation values of each provider. Further, the content information storage unit 122 may store identification information for identifying the provider of the content. Further, the content information storage unit 122 may store information that identifies a user who posted a "good" or "bad" evaluation for each comment. Further, the content information storage unit 122 may add a tag indicating that the content corresponds to the first content to the content corresponding to the first content.

(Action history information storage unit 123)
The behavior history information storage unit 123 according to the embodiment stores various information regarding the user's behavior. FIG. 6 is a diagram illustrating an example of an action history information storage unit according to the embodiment. The behavior history information storage unit 123 shown in FIG. 6 includes items such as "user ID", "behavior ID", "date and time", "type", and "content".

"User ID" indicates identification information for identifying a user. For example, the user identified by user ID "U1" corresponds to user U1 shown in the example of FIG. Furthermore, "behavior ID" indicates information that identifies the user's behavior. “Date and time” indicates the date and time when the corresponding user action was performed. In the example of FIG. 6, "dt11" or the like is shown, but a specific date and time such as "September 8, 2022, 17:07:48" may be stored in the "date and time" field. Furthermore, “type” indicates information regarding the type of behavior of the corresponding user. Moreover, "content" indicates the content targeted in the corresponding user's action.

The example in FIG. 6 indicates that the user (user U1) identified by the user ID "U1" has performed the behavior (behavior AC11) identified by the behavior ID "AC11". For example, the example shown in FIG. 6 indicates that the user U1 purchased the manga B1-1, which is the first volume of the manga B1, at the date and time dt11 (action AC11). Furthermore, it is indicated that the user U1 performed the action (action AC12) identified by the action ID "AC12". For example, in the example shown in FIG. 6, the user U1 has posted a comment CM1 stating that the comic B1 is interesting (action AC12) at date and time dt12.

Further, the user (user U3) identified by the user ID "U3" performs the action (action AC21) identified by the action ID "AC21". For example, the example shown in FIG. 6 indicates that the user U3 purchased the manga B1-3, which is the third volume of the manga B1, at date and time dt21 (action AC21).

Note that the action history information storage unit 123 is not limited to the above, and may store various information depending on the purpose. Further, although FIG. 6 shows a case where behavior information is stored in the behavior history information storage unit 123 for each user ID, the behavior information is not limited to each user ID, and may be stored in chronological order, for example.

(Innovator degree information storage unit 124)
The innovator level information storage unit 124 according to the embodiment stores various information related to the innovator level indicating the degree of influence of a user on other users. FIG. 7 is a diagram illustrating an example of an innovator level information storage unit according to the embodiment. The innovator level information storage unit 124 shown in FIG. 7 includes items such as "user ID,""innovatorlevel," and "category."

"User ID" indicates identification information for identifying a user. “Innovator level” indicates the innovator level estimated for the user. In the example of FIG. 6, the innovator degree is abstractly shown as "SC1" or the like, but the innovator degree is a concrete numerical value.

"Category" indicates to which category the corresponding user's innovator level belongs. Note that in the example of FIG. 6, the category is abstractly shown as "CG1", etc., but concrete categories such as "books" and "sports" are shown, for example. Further, when the "category" is "- (hyphen)", the innovator level indicates the innovator level of the user without limiting the category.

For example, for the user (user U1) identified by the user ID "U1", the innovator degree regarding the category "CG1" in the group GP1 is "SC1". For example, the category "CG1" is a category related to comics. Note that the category is not limited to categories such as comics and dramas, but may be more detailed categories such as boys' comics, girls' comics, detective dramas, romantic dramas, and the like.

Note that the innovator level information storage unit 124 is not limited to the above, and may store various information depending on the purpose. For example, the innovator level information storage unit 124 may store information indicating the date and time when the innovator level was estimated in association with the innovator level.

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

As shown in FIG. 3, the control unit 130 includes an acquisition unit 131, a determination unit 132, an estimation unit 133, and a provision unit 134, and realizes or executes information processing functions and operations described below. . Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 3, and may be any other configuration as long as it performs information processing to be described later.

(Acquisition unit 131)
The acquisition unit 131 acquires various information. For example, the acquisition unit 131 acquires various information from the storage units 120, such as the user information storage unit 121, the content information storage unit 122, the action history information storage unit 123, and the innovator level information storage unit 124. For example, the acquisition unit 131 receives various information from an external information processing device such as the user terminal 10. The acquisition unit 131 acquires history information indicating the user's behavior history.

The acquisition unit 131 obtains behavior information of a target user, who is a user who performed a predetermined behavior before the first content satisfied the evaluation condition, with respect to the first content that satisfies the evaluation condition, which is a condition regarding the evaluation of the content. get. The acquisition unit 131 acquires behavior information of a target user determined to be an innovator regarding the content.

The acquisition unit 131 acquires behavior information of a target user who has performed a predetermined behavior with respect to the first content that is divided into a plurality of work groups and provided. The acquisition unit 131 acquires behavior information of a target user who has performed a predetermined behavior with respect to the first content, which is a manga provided in multiple volumes. The acquisition unit 131 acquires behavior information of a target user who has performed a predetermined behavior with respect to the first content that satisfies the evaluation conditions regarding the award regarding the content. The acquisition unit 131 acquires behavior information of a target user who performed a predetermined behavior with respect to the first content that won an award regarding the content.

The acquisition unit 131 acquires behavior information of a target user who has performed a predetermined behavior with respect to the first content that satisfies the evaluation condition regarding sales. The acquisition unit 131 acquires behavior information of a target user who performed a predetermined behavior with respect to the first content whose sales reached a predetermined value or more. The acquisition unit 131 acquires behavior information of a target user who has performed a predetermined behavior with respect to first content that satisfies evaluation conditions regarding user posting on the Internet. The acquisition unit 131 acquires behavior information of a target user who has performed a predetermined action on the first content that has been posted by a user a predetermined number of times or more.

The acquisition unit 131 extracts various information. The acquisition unit 131 extracts target information from various types of information. For example, the acquisition unit 131 extracts various information from the storage units 120, such as the user information storage unit 121, the content information storage unit 122, the action history information storage unit 123, and the innovator level information storage unit 124.

The acquisition unit 131 extracts, from among the plurality of contents, content that satisfies an evaluation condition that is a condition regarding evaluation of content as a first content. The acquisition unit 131 extracts, as first content, content that satisfies an evaluation condition that is a condition for evaluating content, from among a plurality of contents that are divided into a plurality of work groups and provided. The acquisition unit 131 extracts, as first content, content that satisfies an evaluation condition, which is a condition regarding evaluation of content, from among a plurality of contents, each of which is a plurality of comics provided in a plurality of volumes.

The acquisition unit 131 extracts content that satisfies evaluation conditions regarding awards regarding content from among the plurality of contents as first content. The acquisition unit 131 extracts content that has won an award regarding content from among the plurality of contents as the first content. The acquisition unit 131 extracts content that satisfies the evaluation condition regarding sales from among the plurality of contents as the first content. The acquisition unit 131 extracts the content whose sales have reached a predetermined value or more from among the plurality of contents as the first content. The acquisition unit 131 extracts, from among the plurality of contents, content that satisfies evaluation conditions regarding user posting on the Internet as first content. The acquisition unit 131 extracts content that has been posted by users a predetermined number of times or more from among the plurality of contents as first content.

The acquisition unit 131 extracts, as second content, a content that does not satisfy an evaluation condition, which is a condition regarding content evaluation, from among the plurality of contents. The acquisition unit 131 extracts content that does not satisfy the evaluation condition at the time of processing from among the plurality of contents as second content.

The acquisition unit 131 performs a predetermined action on a first content that satisfies an evaluation condition, which is a condition regarding content evaluation, among a user group including a plurality of users, at a time before the first content satisfies the evaluation condition. Extract users as target users. The acquisition unit 131 performs a predetermined action on a first content that satisfies an evaluation condition, which is a condition regarding content evaluation, among a plurality of users' behavior information groups, at a time before the first content satisfies the evaluation condition. The behavior information of the target user, who is the user who has been identified, is extracted. The acquisition unit 131 extracts behavioral information of a target user determined to be an innovator regarding the content from a group of behavioral information of a plurality of users.

The acquisition unit 131 extracts behavior information of a target user who performed a predetermined behavior with respect to the first content that is divided into a plurality of work groups and provided from among the behavior information group of the plurality of users. The acquisition unit 131 extracts behavior information of a target user who has performed a predetermined behavior with respect to the first content, which is a manga provided in multiple volumes. The acquisition unit 131 extracts, from among a group of behavior information of a plurality of users, behavior information of a target user who performed a predetermined behavior with respect to the first content that satisfies the evaluation condition regarding the award regarding the content. The acquisition unit 131 extracts, from among a group of behavior information of a plurality of users, behavior information of a target user who performed a predetermined behavior with respect to the first content that won an award regarding the content.

The acquisition unit 131 extracts, from among a group of behavior information of a plurality of users, behavior information of a target user who has performed a predetermined behavior with respect to the first content that satisfies the evaluation condition regarding sales. The acquisition unit 131 extracts behavior information of a target user who performed a predetermined behavior for a first content whose sales reached a predetermined value or more from among a group of behavior information of a plurality of users. The acquisition unit 131 extracts, from among a group of behavior information of a plurality of users, behavior information of a target user who has performed a predetermined behavior with respect to a first content that satisfies evaluation conditions regarding user posting on the Internet. The acquisition unit 131 extracts, from among a group of behavior information of a plurality of users, behavior information of a target user who has performed a predetermined behavior with respect to a first content that has been posted by a user a predetermined number of times or more.

(Decision unit 132)
The determining unit 132 executes determination processing to determine various information. The determining unit 132 determines various information based on the various information stored in the storage unit 120. The determining unit 132 determines various information based on the various information acquired by the acquiring unit 131.

The determining unit 132 determines various information regarding the user. The determining unit 132 determines the reliability of the target user based on the target user's behavior information. The determining unit 132 determines a reliability level indicating the degree of the target user's ability as an innovator.

For example, the determining unit 132 executes a process of analyzing character information included in input information such as a comment posted by a user, using natural language processing techniques such as morphological analysis as appropriate. The determining unit 132 specifies (determines) the content of the comment by semantically analyzing the text information of the message. The determining unit 132 specifies (determines) the content of the character information by analyzing the character information using semantic analysis as appropriate. For example, the determining unit 132 determines the content of the character information by appropriately analyzing the character information using various conventional techniques such as syntactic analysis.

Furthermore, when image information is included in the input information posted by the user, the determining unit 132 executes a process of analyzing the image information included in the input information using techniques such as image analysis as appropriate. Further, when the input information includes voice information, the determining unit 132 executes a process of analyzing the voice information included in the input information using a technique such as automatic speech recognition (ASR) as appropriate. For example, the determining unit 132 converts the audio information included in the input information into text, and uses the textual information (character information) to specify (determine) the content of the audio information.

The determining unit 132 executes calculation processing to calculate various information. The determining unit 132 calculates various information based on the various information stored in the storage unit 120. The determining unit 132 calculates various information based on the various information acquired by the acquiring unit 131. The determining unit 132 calculates the reliability of the target user based on the target user's behavior information. The determining unit 132 calculates a reliability level indicating the degree of the target user's ability as an innovator.

(Estimation unit 133)
The estimation unit 133 estimates various information. The estimation unit 133 estimates various information. For example, the estimation unit 133 performs estimation based on various information obtained from external information processing devices such as the user terminal 10 and the service providing device 20. For example, the estimation unit 133 performs estimation based on various information stored in the storage unit 120. For example, the estimation unit 133 performs estimation based on the information determined by the determination unit 132.

Based on the behavior information of the target user, the estimation unit 133 determines whether the second content, which is content in which the target user has performed a predetermined behavior and which does not satisfy the evaluation conditions at the time of processing, is Later, it is estimated whether the evaluation conditions are satisfied. The estimating unit 133 estimates whether the second content in which the target user, who is an innovator, has performed a predetermined action will satisfy the evaluation condition in the future.

The estimation unit 133 estimates whether the second content, which is divided into multiple work groups and provided, will satisfy the evaluation conditions in the future. The estimation unit 133 estimates whether the second content, which is a manga provided in multiple volumes, will satisfy the evaluation conditions in the future. The estimation unit 133 estimates whether the second content, in which the target user has performed a specified action, will satisfy the evaluation conditions related to an award in the future. The estimation unit 133 estimates whether the second content, in which the target user has performed a specified action, will win an award in the future.

The estimation unit 133 estimates whether the second content in which the target user performed a predetermined action will satisfy an evaluation condition related to sales in the future. The estimation unit 133 estimates whether the sales of the second content in which the target user performed a predetermined action will reach a predetermined value in the future. The estimation unit 133 estimates whether the second content in which the target user performed a predetermined action will satisfy an evaluation condition related to a user's post in the future. The estimation unit 133 estimates whether the user's post related to the second content in which the target user performed a predetermined action will reach a predetermined number in the future.

The estimation unit 133 estimates whether the second content satisfies the evaluation condition based on the number of target users who have performed a predetermined action with respect to the second content. The estimation unit 133 estimates whether the second content satisfies the evaluation condition based on the reliability of the target user. The estimating unit 133 estimates whether the second content satisfies the evaluation condition based on the reliability indicating the degree of the target user's ability as an innovator.

The estimation unit 133 calculates a score regarding the evaluation of the second content based on the reliability of the target user, and estimates whether the second content satisfies the evaluation condition based on the score of the second content. The estimation unit 133 calculates a higher score for the second content as the reliability of the target user is higher, and estimates whether the second content satisfies the evaluation condition based on the score of the second content.

The estimation unit 133 estimates whether the second content satisfies the evaluation condition based on a comparison between the score of the second content and a threshold related to evaluation. The estimation unit 133 estimates that the second content satisfies the evaluation condition when the score of the second content is equal to or greater than the threshold value.

The estimation unit 133 executes a calculation process to calculate various pieces of information. The estimation unit 133 calculates various pieces of information based on the various pieces of information stored in the storage unit 120. The estimation unit 133 calculates various pieces of information based on the various pieces of information acquired by the acquisition unit 131.

The estimation unit 133 calculates a score regarding the evaluation of the second content based on the reliability of the target user. The estimation unit 133 calculates a higher score of the second content as the reliability of the target user is higher.

The estimation unit 133 executes generation processing to generate various information. The estimation unit 133 generates various information based on the various information stored in the storage unit 120. For example, the estimation unit 133 also functions as a generation unit that generates various information. The estimation unit 133 generates various information. For example, the estimation unit 133 generates various information from information stored in the user information storage unit 121, the content information storage unit 122, the action history information storage unit 123, the innovator level information storage unit 124, and the like.

The estimating unit 133 generates various information provided by the providing unit 134. If the score of the content X is equal to or greater than the threshold, the estimating unit 133 generates provision information indicating the estimation result such as "It is estimated that the content X satisfies the conditions regarding future evaluation."

(Providing unit 134)
The providing unit 134 provides various information. The providing unit 134 provides various information to an external information processing device. For example, the providing unit 134 provides various information to the user terminal 10 and the service providing device 20. The providing unit 134 transmits various information to the user terminal 10 and the service providing device 20. The providing unit 134 provides various information based on the various information acquired by the acquiring unit 131. The providing unit 134 provides various information according to the determination made by the determining unit 132. The providing unit 134 provides various information according to the estimation by the estimating unit 133.

The providing unit 134 provides a service using the estimation result by the estimating unit 133. The providing unit 134 provides the providing information generated by the estimating unit 133 to a device used by the information providing destination. The providing unit 134 sends provision information indicating an estimation result such as "Content X is estimated to satisfy conditions regarding future evaluation" to a provider device used by a provider of Content Send.

[3. Information processing flow]
Next, the procedure of information processing by the information processing system 1 according to the embodiment will be described using FIG. 8. FIG. 8 is a flowchart illustrating an example of information processing according to the embodiment.

As shown in FIG. 8, the information processing device 100 stores information about a user who has performed a predetermined action on a first content that satisfies an evaluation condition, which is a condition regarding content evaluation, before the first content satisfies the evaluation condition. The behavior information of the target user is acquired (step S101). For example, the information processing device 100 may detect a target user, who is a user who has performed a predetermined action before the first content satisfies the evaluation condition, with respect to the first content that satisfies the evaluation condition, which is a condition regarding the evaluation of the content. Obtain behavioral information.

Further, the information processing device 100 processes the second content, which is the content for which the target user has performed a predetermined behavior and does not satisfy the evaluation condition at the time of processing, based on the behavior information of the target user. It is estimated whether the evaluation condition is satisfied after the point in time (step S102). For example, based on the behavior information of the target user, the information processing device 100 processes the second content, which is the content in which the target user performed a predetermined behavior, and which does not satisfy the evaluation condition at the time of processing. Estimate whether the evaluation condition is satisfied after the point in time.

[4. effect〕
As described above, the information processing apparatus 100 according to the embodiment includes the acquisition section 131 and the estimation section 133. The acquisition unit 131 obtains behavior information of a target user, who is a user who performed a predetermined behavior before the first content satisfied the evaluation condition, with respect to the first content that satisfies the evaluation condition, which is a condition regarding the evaluation of the content. get. Based on the behavior information of the target user, the estimation unit 133 determines whether the second content, which is content in which the target user has performed a predetermined behavior and which does not satisfy the evaluation conditions at the time of processing, is Later, it is estimated whether the evaluation conditions are satisfied.

In this way, the information processing apparatus 100 according to the embodiment performs a second content based on the behavior information of the target user who performed a predetermined behavior with respect to the first content at a time before the first content satisfies the evaluation condition. By estimating whether the content satisfies the evaluation condition after the time of processing, it is possible to appropriately estimate whether the content satisfies the evaluation condition.

Furthermore, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires behavior information of a target user determined to be an innovator regarding content. The estimation unit 133 estimates whether the second content in which the target user, who is an innovator, has performed a predetermined action will satisfy the evaluation condition in the future.

In this way, the information processing device 100 according to the embodiment estimates whether the second content, in which the target user who is an innovator has performed a predetermined action, will satisfy the evaluation condition in the future. can be estimated appropriately.

Furthermore, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires behavior information of a target user who has performed a predetermined behavior with respect to the first content that is divided into a plurality of work groups and provided. The estimating unit 133 estimates whether the second content, which is divided into a plurality of work groups and provided, will satisfy the evaluation condition in the future.

In this way, the information processing apparatus 100 according to the embodiment estimates whether the second content divided into a plurality of works and provided will satisfy the evaluation condition in the future, thereby determining whether the content satisfies the evaluation condition. can be estimated appropriately.

Furthermore, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires behavior information of a target user who has performed a predetermined behavior with respect to the first content, which is a manga provided in multiple volumes. The estimating unit 133 estimates whether the second content, which is a manga provided in multiple volumes, will satisfy the evaluation condition in the future.

In this way, the information processing device 100 according to the embodiment appropriately determines whether the content satisfies the evaluation condition by estimating whether the second content, which is a manga provided with a plurality of volumes, will satisfy the evaluation condition in the future. It can be estimated that

Furthermore, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires behavior information of a target user who has performed a predetermined behavior with respect to the first content that satisfies the evaluation condition regarding the award regarding the content. The estimating unit 133 estimates whether the second content for which the target user has performed a predetermined action will satisfy the evaluation condition regarding the award in the future.

In this way, the information processing device 100 according to the embodiment estimates whether the second content for which the target user has performed a predetermined action will satisfy the evaluation condition regarding the award in the future, thereby determining whether the content satisfies the evaluation condition regarding the award. can be estimated appropriately.

Furthermore, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires behavior information of a target user who performed a predetermined behavior with respect to the first content that won an award regarding the content. The estimation unit 133 estimates whether the second content for which the target user has performed a predetermined action will receive an award in the future.

In this way, the information processing device 100 according to the embodiment appropriately determines whether the content satisfies the evaluation conditions by estimating whether the second content for which the target user has performed a predetermined action will receive an award in the future. It can be estimated.

Furthermore, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires behavior information of a target user who has performed a predetermined behavior with respect to the first content that satisfies the evaluation condition regarding sales. The estimation unit 133 estimates whether the second content for which the target user has performed a predetermined action will satisfy the evaluation condition regarding sales in the future.

In this way, the information processing device 100 according to the embodiment estimates whether the second content for which the target user has performed a predetermined action will satisfy the evaluation condition regarding sales in the future. can be estimated appropriately.

Furthermore, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires behavior information of a target user who has performed a predetermined action on the first content whose sales have reached a predetermined value or more. The estimation unit 133 estimates whether the sales of the second content for which the target user has performed a predetermined action will reach a predetermined value in the future.

In this way, the information processing device 100 according to the embodiment estimates whether the sales of the second content for which the target user has performed a predetermined action will reach a predetermined value in the future, and thereby determines whether the content satisfies the conditions regarding evaluation. can be estimated appropriately.

Furthermore, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires behavior information of a target user who has performed a predetermined behavior with respect to the first content that satisfies the evaluation condition regarding user posting on the Internet. The estimating unit 133 estimates whether the second content for which the target user has performed a predetermined action will satisfy the evaluation condition regarding the user's posting in the future.

In this way, the information processing device 100 according to the embodiment estimates whether the second content for which the target user has performed a predetermined action will satisfy the evaluation conditions regarding the user's posting in the future, so that the content will satisfy the evaluation conditions. can be appropriately estimated.

Furthermore, in the information processing apparatus 100 according to the embodiment, the acquisition unit 131 acquires behavior information of a target user who has performed a predetermined action on the first content that has been posted by a user a predetermined number of times or more. The estimating unit 133 estimates whether the user's posts regarding the second content in which the target user performed a predetermined action will reach a predetermined number of times in the future.

In this way, the information processing device 100 according to the embodiment allows the content to meet the evaluation conditions by estimating whether the user's posts regarding the second content for which the target user has performed a predetermined action will reach a predetermined number of times in the future. It is possible to appropriately estimate whether the requirements are met.

Furthermore, in the information processing apparatus 100 according to the embodiment, the estimation unit 133 estimates whether the second content satisfies the evaluation condition based on the number of target users who have performed a predetermined action with respect to the second content.

In this way, the information processing apparatus 100 according to the embodiment estimates whether the second content satisfies the evaluation condition based on the number of target users who have performed a predetermined action with respect to the second content. It is possible to appropriately estimate whether the evaluation conditions are satisfied.

Further, the information processing device 100 according to the embodiment includes a determining unit 132. The determining unit 132 determines the reliability of the target user based on the target user's behavior information. The estimation unit 133 estimates whether the second content satisfies the evaluation condition based on the reliability of the target user.

In this way, the information processing device 100 according to the embodiment estimates whether the second content satisfies the evaluation condition based on the reliability of the target user, thereby appropriately estimating whether the content satisfies the evaluation condition. can do.

Furthermore, in the information processing apparatus 100 according to the embodiment, the determining unit 132 determines a reliability level indicating the degree of the target user's ability as an innovator. The estimating unit 133 estimates whether the second content satisfies the evaluation condition based on the reliability indicating the degree of the target user's ability as an innovator.

In this way, the information processing device 100 according to the embodiment estimates whether the second content satisfies the evaluation condition based on the reliability indicating the degree of the target user's power as an innovator, so that the content is related to the evaluation. It is possible to appropriately estimate whether the conditions are met.

Furthermore, in the information processing apparatus 100 according to the embodiment, the estimating unit 133 calculates a score regarding the evaluation of the second content based on the reliability of the target user, and based on the score of the second content, the estimation unit 133 Estimate whether the conditions are met.

In this way, the information processing apparatus 100 according to the embodiment calculates a score regarding the evaluation of the second content based on the reliability of the target user, and based on the score of the second content, the second content satisfies the evaluation condition. By estimating this, it is possible to appropriately estimate whether the content satisfies the evaluation conditions.

Furthermore, in the information processing apparatus 100 according to the embodiment, the estimation unit 133 calculates the score of the second content to be higher as the reliability of the target user is higher, and the second content is evaluated based on the score of the second content. Estimate whether the condition is met.

In this way, the information processing device 100 according to the embodiment calculates the score of the second content higher as the reliability of the target user is higher, and the second content satisfies the evaluation condition based on the score of the second content. By estimating this, it is possible to appropriately estimate whether the content satisfies the evaluation conditions.

Furthermore, in the information processing device 100 according to the embodiment, the estimating unit 133 estimates whether the second content satisfies the evaluation condition based on a comparison between the score of the second content and a threshold related to evaluation.

In this way, the information processing device 100 according to the embodiment estimates whether the second content satisfies the evaluation condition based on the comparison between the score of the second content and the evaluation threshold, so that the content can meet the evaluation condition. It is possible to appropriately estimate whether the following conditions are satisfied.

Furthermore, in the information processing apparatus 100 according to the embodiment, the estimation unit 133 estimates that the second content satisfies the evaluation condition when the score of the second content is equal to or greater than the threshold value.

In this way, the information processing apparatus 100 according to the embodiment estimates that the second content satisfies the evaluation condition when the score of the second content is equal to or higher than the threshold value, thereby appropriately determining whether the content satisfies the evaluation condition. It can be estimated that

Further, the information processing device 100 according to the embodiment includes a providing unit 134. The providing unit 134 provides a service using the estimation result by the estimating unit 133.

In this way, the information processing apparatus 100 according to the embodiment can provide a service using estimation results.

[5. Hardware configuration]
The information processing apparatus 100 according to the embodiments described above is realized, for example, by a computer 1000 having a configuration as shown in FIG. FIG. 9 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing device. The computer 1000 includes a CPU 1100, a RAM 1200, a ROM (Read Only Memory) 1300, an HDD (Hard Disk Drive) 1400, a communication interface (I/F) 1500, an input/output interface (I/F) 1600, and a media interface (I/F). ) has 1700.

CPU 1100 operates based on a program stored in ROM 1300 or HDD 1400, and controls each section. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started, programs depending on the hardware of the computer 1000, and the like.

The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. Communication interface 1500 receives data from other devices via network N and sends it to CPU 1100, and sends data generated by CPU 1100 to other devices via network N.

The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and mouse via an input/output interface 1600. CPU 1100 obtains data from an input device via input/output interface 1600. Further, CPU 1100 outputs the generated 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 it 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) or a PD (Phase change rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

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

As mentioned above, some embodiments of the present application have been described in detail based on the drawings, but these are merely examples, and various modifications and variations can be made based on the knowledge of those skilled in the art, including the embodiments described in the disclosure section of the invention. It is possible to carry out the invention in other forms with modifications.

[6. others〕
Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or the processes described as being performed manually can be performed manually. All or part of the process can also be performed automatically using known methods. In addition, information including the processing procedures, specific names, and various data and parameters shown in the above documents and drawings may be changed arbitrarily, unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

In addition, each component of each device shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

Furthermore, the processes described in the embodiments described above can be combined as appropriate within a range that does not conflict with the process contents.

Further, the above-mentioned "section, module, unit" can be read as "means", "circuit", etc. For example, the acquisition unit can be read as an acquisition means or an acquisition circuit.

1 Information processing system 100 Information processing device 121 User information storage unit 122 Content information storage unit 123 Action history information storage unit 124 Innovator level information storage unit 130 Control unit 131 Acquisition unit 132 Determination unit 133 Estimation unit 134 Provision unit 10 User terminal 20 Service Providing device N Network

Claims (20)

Obtaining behavior information of a target user who is a user who has performed a predetermined behavior at a time before the first content satisfies the evaluation condition with respect to the first content that satisfies the evaluation condition that is a condition regarding the evaluation of the content. Department and
Based on the behavior information of the target user, the second content, which is the content in which the target user performed the predetermined behavior, and which does not satisfy the evaluation condition at the time of processing, is an estimation unit that estimates whether the evaluation condition is satisfied later;
An information processing device comprising: The acquisition unit includes:
obtaining the behavioral information of the target user determined by an innovator regarding the content;
The estimation unit is
The information processing apparatus according to claim 1, further comprising: estimating whether the second content for which the target user, who is the innovator, has performed the predetermined action will satisfy the evaluation condition in the future. The acquisition unit includes:
acquiring the behavior information of the target user who has performed the predetermined behavior with respect to the first content provided divided into a plurality of work groups;
The estimation unit is
The information processing apparatus according to claim 1, further comprising: estimating whether the second content, which is divided into a plurality of work groups and provided, satisfies the evaluation condition in the future. The acquisition unit includes:
obtaining the behavior information of the target user who has performed the predetermined behavior with respect to the first content, which is a manga provided in multiple volumes;
The estimation unit is
The information processing apparatus according to claim 1, wherein the information processing apparatus estimates whether the second content, which is a manga provided in a plurality of volumes, will satisfy the evaluation condition in the future. The acquisition unit includes:
acquiring the behavior information of the target user who performed the predetermined behavior with respect to the first content that satisfies the evaluation conditions regarding the award regarding the content;
The estimation unit is
The information processing apparatus according to claim 1, further comprising: estimating whether the second content for which the target user has performed the predetermined action will satisfy the evaluation condition regarding the award in the future. The acquisition unit includes:
acquiring the behavior information of the target user who performed the predetermined behavior with respect to the first content that won a content-related award;
The estimation unit is
The information processing device according to claim 5, further comprising: estimating whether the second content for which the target user performed the predetermined action will win the award in the future. The acquisition unit includes:
acquiring the behavior information of the target user who performed the predetermined behavior with respect to the first content that satisfies the evaluation condition regarding sales;
The estimation unit is
The information processing apparatus according to claim 1, further comprising: estimating whether the second content for which the target user has performed the predetermined action will satisfy the evaluation condition regarding the sales in the future. The acquisition unit is
acquiring the behavioral information of the target user who has performed the predetermined behavior on the first content that has achieved sales of a predetermined value or more;
The estimation unit is
The information processing device according to claim 7 , further comprising: an estimation unit that estimates whether the sales of the second content in which the target user has performed the predetermined action will reach the predetermined value in the future. The acquisition unit includes:
acquiring the behavior information of the target user who has performed the predetermined behavior with respect to the first content that satisfies the evaluation condition regarding user posting on the Internet;
The estimation unit is
The information processing apparatus according to claim 1, further comprising: estimating whether the second content for which the target user has performed the predetermined action will satisfy the evaluation condition regarding the user's posting in the future. The acquisition unit includes:
acquiring the behavior information of the target user who has performed the predetermined behavior with respect to the first content that has been posted by the user a predetermined number of times or more;
The estimation unit is
The information processing apparatus according to claim 9, further comprising: estimating whether the number of posts by the user regarding the second content for which the target user performed the predetermined action will reach the predetermined number of times in the future. The estimation unit is
Information processing according to claim 1, characterized in that it is estimated whether the second content satisfies the evaluation condition based on the number of the target users who performed the predetermined action with respect to the second content. Device. a determining unit that determines the reliability of the target user based on behavior information of the target user;
Furthermore,
The estimation unit is
The information processing apparatus according to claim 1, wherein it is estimated whether the second content satisfies the evaluation condition based on the reliability of the target user. The determining unit is
determining the reliability level indicating the degree of power of the target user as an innovator;
The estimation unit is
The information processing device according to claim 12, wherein it is estimated whether the second content satisfies the evaluation condition based on the reliability indicating the degree of power of the target user as an innovator. The estimation unit is
calculating a score regarding the evaluation of the second content based on the reliability of the target user, and estimating whether the second content satisfies the evaluation condition based on the score of the second content. The information processing device according to claim 13. The estimation unit is
The higher the reliability of the target user, the higher the score of the second content is calculated, and based on the score of the second content, it is estimated whether the second content satisfies the evaluation condition. The information processing device according to claim 14. The estimation unit is
The information processing apparatus according to claim 14, wherein it is estimated whether the second content satisfies the evaluation condition based on a comparison between the score of the second content and a threshold related to the evaluation. The estimation unit is
The information processing apparatus according to claim 16, wherein when the score of the second content is equal to or greater than the threshold, it is estimated that the second content satisfies the evaluation condition. a providing unit that provides a service using the estimation result by the estimation unit;
The information processing device according to claim 1, further comprising: An information processing method performed by a computer, the method comprising:
Obtaining behavior information of a target user who is a user who has performed a predetermined behavior at a time before the first content satisfies the evaluation condition with respect to the first content that satisfies the evaluation condition that is a condition regarding the evaluation of the content. process and
Based on the behavior information of the target user, the second content, which is the content in which the target user performed the predetermined behavior, and which does not satisfy the evaluation condition at the time of processing, is an estimation step of estimating whether the evaluation condition is satisfied later;
An information processing method characterized by comprising: Obtaining behavior information of a target user who has performed a predetermined behavior at a time before the first content satisfies the evaluation condition with respect to the first content that satisfies the evaluation condition that is a condition regarding the evaluation of the content. steps and
Based on the behavior information of the target user, the second content, which is the content in which the target user performed the predetermined behavior, and which does not satisfy the evaluation condition at the time of processing, is an estimation procedure for estimating whether the evaluation condition is satisfied later;
An information processing program that causes a computer to execute.

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