JP4374417B1 - Information analysis apparatus and information analysis program - Google Patents

Abstract

To provide an information analysis apparatus and an information analysis program capable of discovering information having high propagating property early without depending on the content of the information.
An information analysis apparatus connected to an information providing apparatus for storing information propagated by an information propagator via a network so as to communicate with the information provider. An information acquisition unit 12a that acquires a propagation distance corresponding to the number of information propagation chains, the number of propagation of a plurality of information propagators who performed propagation, and a classification to which the information propagator who performed the propagation belongs, and this information acquisition unit The weighted average propagation distance indicating the possibility of information propagation is calculated based on the propagation distance and propagation number acquired in 12a and the weighting factor determined based on the classification acquired by the information acquisition means. The calculating part 12b is provided.
[Selection] Figure 1

Description

  The present invention relates to an information analysis apparatus and an information analysis program for analyzing various types of information transmitted by an information propagator on a WEB.

  2. Description of the Related Art Conventionally, in order to develop a new market and predict demand, a method for predicting the fashion of products and services based on information transmitted on the Web such as a blog or SNS (Social Networking Service) has been proposed.

  For example, a trend prediction device that extracts keywords extracted from information such as blog articles, quantifies the usage status of the keywords, and monitors the quantified keyword usage status in time series, thereby predicting a trend in the near future Has been proposed (see, for example, Patent Document 1).

  However, in such a conventional method, the prediction is performed depending on the keyword “information content”, so that the information content is appropriately set at the initial stage of propagation when the information content itself is unclear. It was difficult to do so, and it was only possible to predict information that had already been propagated to some extent. Alternatively, there are cases where the keyword to be monitored is intentionally replaced with a secret word or abbreviation for some reason and information is transmitted. In such a case, the keyword is substantially the same as the information indicated by the keyword. Although it is information, it may not be grasped as information including the keyword, and it may be difficult to assume the keyword itself.

  Accordingly, the inventors of the present application have proposed a method of making a prediction by paying attention not to the content of information but to an “information propagation form” among a plurality of information propagators. In this method, the information propagation form is a tree structure in which the information propagator that is the information propagation source is “parent” and the information propagator that is the information propagation destination is “child” (hereinafter “transmission tree”). )), An “average propagation distance” that is an index indicating an average propagation distance of information is calculated, and the propagation form of information is evaluated based on the average propagation distance. For example, information that tends to have a long average propagation distance tends to be judged as interesting or important information for the user. According to such a method, information propagation can be predicted without depending on “content of information”, and even if the initial stage of propagation or the content of information is intentionally altered, There is a possibility that information can be discovered early (see, for example, Non-Patent Document 1).

JP 2006-227965 A Satoshi Takeuchi, Tsubasa Ohno, Masanori Akiyoshi, Norihisa Kouda, “Characteristic Evaluation of Transmission Forms by Word-of-mouth Communication for Predicting Information Propagation on the Internet”, Institute of Electrical Engineers, Information Systems Study Group, IS-07-19, 21- 26 pages, 29 June 2007

  Here, generally, the information propagator who propagates information via a blog or SNS can be classified according to the degree of influence in information propagation. For example, “Cyber bloggers” that focus on items that are likely to become epidemic early, and to some extent for other information disseminators who are late in focusing on items that are likely to become epidemic compared to this cyber blogger Can be classified into “opinion leaders” having the influence of “general” and “general bloggers” not corresponding to these opinion leaders or cyber bloggers. Information propagated across classifications, such as information propagated from cyber bloggers to opinion leaders and information propagated from opinion leaders to general bloggers, is simply changed to information propagated within the same classification. Compared to this, it is considered that the information has high propagating properties.

  However, the information propagation prediction method using the average propagation distance proposed by the inventors of the present application in Non-Patent Document 1 does not consider the degree of influence of such an information propagater, and information propagation is performed at the time of information propagation. There was no difference in the propagation distance of information between the case where the person's classification was straddled and the case where the person was not straddled. Therefore, it is possible to make a difference in the evaluation of propagation patterns between information judged to be important by information propagators in multiple categories and information judged to be important only by information propagators in a single category. Therefore, there is a possibility that the fact that information is propagated across the classification cannot be reflected in the information propagation prediction.

  The present invention has been made in view of the above, and provides an information analysis apparatus and an information analysis program that can discover information having high propagating properties early without depending on the content of the information. With the goal.

  According to the information analysis apparatus or the information analysis program according to claim 1, 2, or 6, the propagation distance corresponding to the number of chain propagation of information through a plurality of information propagators and the plurality of propagation The weighted average propagation distance is calculated based on the number of information propagators and the weighting factor based on the classification to which the propagating information propagator belongs. Thus, since the fact that the information has been propagated across the categories of information propagators can be reflected in the propagation prediction, it is possible to find information with high propagating properties early without depending on the content of the information.

  According to the information analysis apparatus of claim 3, the average propagation distance is calculated based on the propagation distance and the number of propagation persons for each of a plurality of pieces of information, and the regression between the calculated average propagation distance and the number of propagation persons is performed. Calculate the reference propagation distance by substituting the propagation number of the information to be analyzed into the regression equation and calculate the propagation power of the information based on the reference propagation distance and the weighted average propagation distance of the information to be analyzed. Therefore, an objective index capable of comparing the propagation power of information can be obtained regardless of the number of people who transmit the information to be analyzed.

  In addition, according to the information analysis device of the fourth aspect, by automatically determining the possibility of propagation of the information to be analyzed using the reference value, the information having high propagation property is changed to the content of the information. It becomes possible to grasp accurately and quickly without depending on it.

  Further, according to the information analysis apparatus according to claim 5, the information is information propagated through the blog, the information propagator is a sender of the information by the blog, and the classification is the influence of the blog. Therefore, we consider the possibility of information transmission by blogs that have a great influence on information propagation in recent years, taking into account the classification based on the influence of blog senders. Can be determined.

  Embodiments of an information analysis apparatus and an information analysis program according to the present invention will be described below in detail with reference to the accompanying drawings.

(Constitution)
First, the configuration of the information analysis system will be described. FIG. 1 is an explanatory diagram conceptually showing the overall configuration of the information analysis system. The information analysis system 1 is configured by connecting a plurality of information providing apparatuses 3, a plurality of terminal apparatuses 4, and an information analysis apparatus 10 via a network 2 such as the Internet so that they can communicate with each other.

(Configuration-Information provision device)
The information providing apparatus 3 can be configured as a known Web server such as an SNS server or various blog site servers, and the specific content of the provided information is arbitrary. The information providing device 3 stores information provided by an information propagator in response to a request from the terminal device 4 or the information analysis device 10, or stores the stored information in the terminal device 4 or the information analysis device 10. It has the function to transmit to.

(Configuration-terminal device)
In the terminal device 4, an information propagator inputs / outputs information to / from the information providing device 3, or an analyst using the information analysis system 1 inputs / outputs information to / from the information analyzing device 10. It can be configured as a known personal computer.

(Configuration-Information analyzer)
The information analysis apparatus 10 is configured by connecting a network interface (hereinafter “network IF”) 11, a control unit 12, and a storage unit 13 so that they can communicate with each other via a bus.

  The network IF 11 is a communication control interface for the information analysis apparatus 10 to communicate via the network 2, and is an input unit and an output unit. The network IF 11 is configured as a network board, for example.

  The control unit 12 is a control unit that controls each unit of the information analysis apparatus 10, and includes an information acquisition unit 12a, a calculation unit 12b, and a determination unit 12c in terms of functional concept. The information acquisition unit 12 a is information acquisition means for acquiring propagation information related to the information propagation form from the information providing apparatus 3 via the network 2. The calculating unit 12b is a calculating unit that calculates various numerical values and regression equations described later. The determination unit 12c is a determination unit that determines the possibility of information propagation. Specifically, the control unit 12 includes a CPU (Central Processing Unit), various programs interpreted and executed on the CPU (control programs such as an OS, programs that define various processing procedures, and the like), and An internal memory for storing required programs and required data is provided.

  The storage unit 13 is configured by, for example, a hard disk or other recording medium, and includes a user information database (hereinafter “DB”) 13a and a propagation information DB 13b.

  The user information DB 13a is information propagator storage means for storing information about an information propagator that provides information to the information providing apparatus 3 (hereinafter referred to as user information). As illustrated in FIG. Items include “user ID”, “storage destination”, “classification”, and “weighting coefficient”, and information corresponding to these items is stored in association with each other. Information stored corresponding to the item “user ID” is identification information for uniquely identifying the information propagator. The information stored corresponding to the item “storage location” is information indicating the storage location of the provided information provided by each information propagator (in this case, the information providing device 3). For example, the URL address or RSS (Rich Site) is stored. (Summary or RDF Site Summary). The information stored corresponding to the item “classification” is information for specifying the classification of the information propagator based on a predetermined standard, and is a classification according to the contents of the provided information provided by each information propagator. Information corresponding to “special category” and “class” that is a classification according to the degree of influence in providing information by the information propagator is stored. Examples of information stored corresponding to “class” include information such as “cyber blogger (hereinafter referred to as cyber)”, “opinion reader (hereinafter referred to as OP)”, and “general blogger (hereinafter referred to as general)”. Can be used. The information stored corresponding to the item “weight coefficient” is a weight coefficient used when the calculation unit 12b calculates the weighted average propagation distance. Here, the weight coefficient is based on the classification to which each information propagator belongs. For example, “0” is stored when the information propagator class is cyber, “1” is stored when it is OP, and “2” is stored when it is “general”. The timing and method for storing these pieces of information in the user information DB 13a are arbitrary. For example, the information is input from the terminal device 4 via the network 2 by an analyst and stored in the user information DB 13a.

  The propagation information DB 13b in FIG. 1 is a propagation information storage unit for storing information relating to the propagation form of information (hereinafter, propagation information). As illustrated in FIG. , “Provided user ID”, “propagation user ID”, “number of propagation users”, and “update date”, and information corresponding to these is stored in association with each other. The information stored in correspondence with the item “information ID” is information for uniquely identifying information provided by the information propagator and propagated through other information propagators. The information stored corresponding to the item “provided user ID” is information for identifying the information propagator who first provided each information to the information providing apparatus 3, for example, the user of the information propagator who provided the information ID is stored. The information stored in correspondence with the item “propagation user ID” is information for identifying the information propagator who propagated the information provided to the information providing apparatus 3, for example, the information propagator who propagated the information The user ID is stored in association with the user ID of the information propagation source and the user ID of the transmission destination in the order of propagation of the information. In the example shown in FIG. 2B, information transmitted from the information propagator of UID005 to the information propagator of UID419 is further propagated to the information propagators of UID420 and UID690. Further, in correspondence with this item “propagation user ID”, information for specifying the propagation distance corresponding to the number of times of propagation until the information is propagated to each information propagator is stored along with the user ID. Is done. For example, as shown in FIG. 2B, when the information provided by the information propagator of UID005 is propagated to the information propagator of UID377 via the information propagators of UID419 and UID690, the number of propagation chains is 3 Therefore, the propagation distance “3” is stored in association with the user ID (“UID 377 (3)” in FIG. 2B). The information stored in correspondence with the item “number of propagation persons” is information for specifying the number of propagation persons of a plurality of information propagation persons who have propagated for each piece of information. The information stored corresponding to the item “update date” is information for specifying the date when the contents of the propagation information DB 13b are updated for each information. The timing and method for storing these pieces of information in the propagation information DB 13b are arbitrary. For example, in the information acquisition process described later, the information acquisition unit 12a acquires the information from the information providing device 3 via the network 2, and stores the information in the propagation information DB 13b. Stored.

(processing)
Next, the processing performed by the information analysis apparatus 10 shown in FIG. 1 will be described broadly as information acquisition processing and calculation determination processing.

(Processing-Information acquisition processing)
FIG. 3 is a flowchart of the information acquisition process. By repeatedly executing this information acquisition process, the latest propagation information can always be stored in the propagation information DB 13b.

  As a premise of this information acquisition processing, the analyst specifies the blog of the information propagator who provides information to be analyzed to the information providing apparatus 3 by an arbitrary method, and sets the information related to the information propagator and the blog to the user information DB 13a. To store. Thereafter, when the information analysis apparatus 10 is instructed to start the information acquisition process by a predetermined method, the information acquisition unit 12a refers to the storage location of the user information DB 13a and performs crawling on the information providing apparatus 3 (SA1). It is determined by a known method whether or not information is newly provided by the propagator (SA2).

  Then, the information acquisition unit 12a continues the crawling while the information is not newly provided (SA2, No) (SA1), and when it is determined that the information is newly provided (SA2, Yes), the information is provided. It is determined whether the information (hereinafter “provided information”) has been registered in the propagation information DB 13b (SA3). For example, for this determination, link destination information or track back destination information included in the provided information can be used. Specifically, it is determined whether or not link information or trackback destination information is included in the provision information. If such information is not included, the provision information is a new provision that has not been registered. It is determined that the information is information, and when such information is included, the provision information is determined to be registered provision information.

  And when it determines with provision information being new provision information which has not been registered (SA3, No), the information acquisition part 12a refers to user information DB13a based on the storage location of this provision information, and this The user ID of the information propagator who provided the provided information (hereinafter “provided user”) is specified (SA6). Furthermore, the information acquisition unit 12a assigns a new information ID to the provided information provided by the providing user (SA7). And the information acquisition part 12a updates the content of propagation information DB13b using these user ID and information ID (SA8). That is, the information ID assigned in SA7 is newly stored in the item “information ID”, the user ID specified in SA6 is stored in the item “provided user ID” in association with this information ID, and the update is performed. Store the date in the item "update date".

  On the other hand, when it is determined that the provision information is registered provision information (SA3, Yes), the information acquisition unit 12a refers to the user information DB 13a based on the storage location of the provision information, thereby obtaining the provision information. The user ID of the propagated information propagator (hereinafter “propagation user”) is specified (SA4). Furthermore, the information acquisition unit 12a provides information propagation that provides information (hereinafter referred to as "propagation source information") from which the provision information is propagated based on link destination information and trackback destination information included in the provision information. The user ID of the user (hereinafter referred to as “propagation source user”) is specified (SA5). Thereafter, the information acquisition unit 12a updates the contents of the propagation information DB 13b based on the specified information (SA8). That is, in association with the user ID of the specified propagation source user in the item “provided user ID” or “propagation user ID”, the user ID and propagation distance of the propagation user identified in SA4 are set in the item “propagation user ID”. In addition, the number of propagations corresponding to the user ID of the specified propagation source user is incremented, and the update date corresponding to the user ID of the specified propagation source user is updated. Thereafter, similarly, SA1 to SA8 are recursively performed.

(Processing-Calculation judgment process)
Next, calculation determination processing for calculating various numerical values to determine the possibility of information propagation will be described. FIG. 4 is a flowchart of the calculation determination process. This calculation determination process is started, for example, when an analyst inputs an execution instruction for the calculation determination process from the terminal device 4 to the information analysis apparatus 10 via the network 2. At this time, an information ID for specifying the analysis target information is input to the information analysis apparatus 10 by the analyst.

  When the calculation determination process is activated, the calculation unit 12b refers to the information acquired by the information acquisition unit 12a (here, the information stored in the propagation information DB 13b), and propagates information about each provided information (for example, propagation user) ID, propagation distance, propagation number) are acquired (SB1). Further, the user information DB 13a is referred to based on each acquired propagation user ID, and a weighting factor corresponding to each propagation user ID is acquired (SB2). Then, based on the propagation distance and number of propagation obtained in SB1 and the weighting coefficient obtained in SB2, a weighted average propagation distance (hereinafter referred to as “TAPD”) is calculated for each provided information (hereinafter referred to as “TAPD”). SB3).

This TAPD is calculated using the following calculation formula (where tapd (m) is TAPD, l (m, u) is the propagation distance in the propagation user u that has received the analysis target information m (however, the analysis target) The propagation distance in the providing user u that first provided the information is 0), | R | is the number of propagation, phase (sender) is a weighting factor corresponding to the classification to which the propagation source user sender who provided the analysis target information belongs, phase (u) is a weighting factor corresponding to the classification to which the propagation user u that received the analysis target information belongs, and k is a predetermined weighting constant). In addition, the absolute value for “phase (sender) -phase (u)” is taken not only when information is transmitted from the cyber blogger to the general blogger, but also from the general blogger to the cyber blogger. Even in this case, the fact that the information is propagated across the classifications has the same influence on the propagation prediction.

  In this way, by weighting the propagation distance according to the propagation user classification, it is possible to reflect the effect when information is propagated across propagation users belonging to different classifications in TAPD. it can. For example, when the value of the weighting constant k is larger than 1, information that is propagated across classifications, such as information propagated from cyber to OP and information propagated from OP to the general public, Since TAPD becomes large, it is numerically expressed that information is highly transmitted.

  Subsequently, the calculation unit 12b derives a regression equation between the TAPD calculated in SB3 and the number of persons transmitted using a known mathematical method (SB4). FIG. 5 is a scatter diagram in which data about each provided information is plotted with the number of people on the horizontal axis and the TAPD on the vertical axis, and the straight line in the figure is a regression line corresponding to the regression equation derived by the calculation unit 12b. .

  Returning to FIG. 4, the calculation unit 12b calculates a reference propagation distance corresponding to the analysis target information (SB5). Specifically, the number of propagation persons corresponding to the information ID of the analysis target information specified by the analyst is acquired from the propagation information DB 13b, and the number of propagation numbers of the analysis target information is substituted into the regression equation derived in SB4. Based on this, the standard propagation distance is calculated. For example, a regression equation corresponding to the regression line shown in FIG. 5 (an equation for calculating an average TAPD (= reference propagation distance) corresponding to the number of persons propagated) is “y = 0.0655x + 1.925” (y is If the propagation number corresponding to the information ID of the analysis target information is 266, the reference propagation distance is 19.348.

  Next, the calculation unit 12b calculates an information propagation power index (hereinafter referred to as “IPIX”) by dividing the TAPD by the reference propagation distance (SB6). According to this calculation, based on the correlation obtained from the TAPD of each piece of information and the number of people transmitted, the IPIX as an objective index that is not affected by the size of the number of people transferred. Can be substituted. For example, when the TAPD of the analysis target information is 31.84, when this is divided by the reference propagation distance 19.348, IPIX is obtained as 1.65.

  Thereafter, the determination unit 12c determines the possibility of propagation of the analysis target information based on the IPIX calculated by the calculation unit 12b and transmits the determination result (SB7). For example, the determination unit 12c compares IPIX with a predetermined reference value (here, 1), and when IPIX is larger than the reference value (when TAPD is in a region above the regression line in FIG. 5), the analysis target information If the IPIX is below the reference value (when TAPD is on the regression line or in the region below the regression line in FIG. 5), the analysis target information is unlikely to propagate. It is determined that there is a high possibility that it is propagated intentionally by hoax. For example, when IPIX is obtained as 1.65 as described above, it is determined that the analysis target information is highly likely to be propagated because it is larger than the reference value of 1. And the determination part 12c transmits the information of the predetermined format which shows this determination result to the analyzer's terminal device 4. FIG. In this terminal device 4, information indicating the determination result of the analysis target information is output in a predetermined format, so that the analyst can grasp the prediction result of the propagation of the analysis target information.

[Modifications to Embodiment]
Although the embodiments of the present invention have been described above, the specific configuration and means of the present invention can be arbitrarily modified and improved within the scope of the technical idea of each invention described in the claims. Can do. Hereinafter, such a modification will be described.

(About information acquisition processing)
In the embodiment, in the information acquisition process, the information acquisition unit 12a acquires the content of the propagation information in the propagation information DB 13b from the information providing device 3, but the latest propagation information is transferred to the propagation information DB 13b by any other method. The information may be stored, and the information acquisition unit 12a may acquire propagation information from the propagation information DB 13b as necessary and pass it to the calculation unit 12b.

(About calculation judgment processing)
In the embodiment, it has been described that the calculation unit 12b calculates the TAPD for each provided information in the calculation determination process. However, when the content of the propagation information DB 13b is updated in the information acquisition process, the provided information related to the update is provided. Can be calculated and stored in the propagation information DB 13b. In this case, in the calculation determination process, the calculation unit 12b can acquire the TAPD from the propagation information DB 13b and derive a regression equation between the acquired TAPD and the number of persons transmitted. Since TAPD itself is also effective information for predicting information propagation, only TAPD may be transmitted to the terminal device 4 without deriving a regression equation or calculating IPIX.

(About propagation information DB)
In the embodiment, it has been described that propagation information is stored in the propagation information DB 13b illustrated in FIG. 2B. However, “information ID”, “sender ID”, “receiver ID”, “propagation distance”, “update” Propagation information as list data having “date and time” as a data item may be stored in the storage unit 13. For example, when the information propagator A who first provided the information sends information to the information propagators B and C, “001, userA, userA, 0, 200800810081420”, “001, userA, userB, 1,00810081420” , “001, userA, userC, 1,00810081420” are stored. When B transfers to D, list data such as “001, userB, userD, 2, 20080081530” is stored. In this case, for example, in order to identify the number of people who propagate information corresponding to the information ID “001”, the number of people propagated can be identified by examining the number of list data including the information ID “001”.

(Modification-About distribution and integration)
Further, each of the electrical components described above is functionally conceptual and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each part is not limited to the one shown in the figure, and all or a part thereof may be functionally or physically distributed / integrated in arbitrary units according to various loads and usage conditions. Can be configured. For example, the information analysis device 10 and the information providing device 3 may be integrated with each other.

It is explanatory drawing which shows the whole structure of an information analysis system functionally conceptually. (A) is a table | surface which shows the information stored in user information DB, (b) is a table | surface which shows the information stored in propagation information DB. It is a flowchart of an information acquisition process. It is a flowchart of a calculation determination process. It is the scatter diagram which plotted the data about each provision information by making a horizontal axis the propagation number of persons and a vertical axis | shaft with TAPD.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Information analysis system 2 Network 3 Information provision apparatus 4 Terminal apparatus 10 Information analysis apparatus 11 Network IF
12 control unit 12a information acquisition unit 12b calculation unit 12c determination unit 13 storage unit 13a user information DB
13b Propagation information DB

Claims (6)

An information analysis device connected to be able to communicate via a network with respect to an information providing device that stores information propagated by an information propagator,
A user ID for uniquely identifying the information propagator, a classification to which the information propagator belongs, and a user information DB that stores the weighting coefficient in association with each other;
The user ID information propagation who propagate the information, the propagation distance corresponding to the chain number of the propagation of the information through the plurality of the information propagation person, and the propagation number of the plurality of information propagation who performed the propagation Propagation information DB stored in association with each other;
Based on the propagation distance and the number of propagation people stored in the propagation information DB, and the weighting factor stored in the user information DB in association with the classification corresponding to the user ID of the information propagator who propagated the information Calculating means for calculating a weighted average propagation distance indicating the possibility of propagation of the information;
An information analysis apparatus comprising: The calculating means calculates the weighted average propagation distance using the following calculation formula (where tapd (m) is the weighted average propagation distance and l (m, u) is the information m received: The propagation distance in the information propagator u (provided that the propagation distance in the information propagator u that first provided the information is 0), | R | is the number of propagators, and phase (sender) provides the information A weighting factor corresponding to the classification to which the information propagator sender belongs, phase (u) is a weighting factor corresponding to the classification to which the information propagator u that has received the information belongs, k is a predetermined weighting constant),

The information analysis apparatus according to claim 1. The calculating means is
Calculate the weighted average propagation distance based on the propagation distance and the number of propagation persons for each of a plurality of the information,
Deriving a regression equation between the calculated weighted average propagation distance and the number of propagation persons,
The propagation number for analyte information specified by a predetermined method from among the plurality of the information, a value obtained by substituting the regression equation, a reference propagation distance of the analyte information,
The weighted average propagation distance of the analyte information, a value obtained by dividing the reference propagation distance of the analyte information, the information diffusion force index indicating a propagation force of the analyte information thing,
The information analysis apparatus according to claim 1 or 2, characterized by the above. A determination means for determining the possibility of propagation of the information to be analyzed by comparing the information propagation power index calculated by the calculation means with a predetermined reference value;
The information analysis apparatus according to claim 3, further comprising: The information is information propagated through a blog,
The information propagator is a sender of the information by the blog,
The classification is a classification for classifying the caller based on the influence of the blog;
The information analysis device according to any one of claims 1 to 4, wherein An information analysis program that causes a computer as an information analysis apparatus connected to be able to communicate via a network to an information providing apparatus that stores information propagated by an information propagator,
The computer,
A user ID for uniquely identifying the information propagator, a classification to which the information propagator belongs, and a user information DB that stores the weight coefficient in association with each other;
The user ID of the information propagator who propagated the information, the propagation distance corresponding to the number of chain propagation of the information via the plurality of information propagators, and the number of propagation of the plurality of information propagators who performed the propagation Propagation information DB stored in association with each other;
Based on the propagation distance and the number of propagation people stored in the propagation information DB, and a weighting factor stored in the user information DB in association with the classification corresponding to the user ID of the information propagator who propagated the information Calculating means for calculating a weighted average propagation distance indicating the possibility of propagation of the information;
Information analysis program to function as

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