Server and computer program

Abstract

To provide a technique capable of more efficiently selecting influencers suited to advertisement target products and services.SOLUTION: A server performs the steps of: acquiring vectorized influencer information related to each of a plurality of influencers; acquiring commercial material information related to a commercial material, which is an advertisement target product or service; vectorizing the acquired commercial material information; calculating a similarity score from the vectorized influencer information and the vectorized commercial material information; selecting a first influencer having a high relevance to the commercial material from among the plurality of influencers on the basis of the calculated similarity score; and outputting the first influencer information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a server and a computer program. [Background technology]

[0002] In recent years, advances in communication technology have led to the provision of social networking services (SNS), which allow a wide range of information to be shared among a large number of users. On SNS, any user can disseminate a variety of information, opinions, assertions, reviews, etc., and among these users, those who disseminate information with great influence are called "influencers."

[0003] Influencers are users who have a high degree of influence on a particular platform, and generally have a large number of followers, subscribers, plays, and views. In recent years, "influencer marketing," which utilizes the influence of influencers to promote a target, has been attracting attention. Patent Document 1 discloses a technology that mediates between advertisers and influencers who are suitable for the product or service being advertised. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2023-535974 Summary of the Invention [Problem to be solved by the invention]

[0005] The present invention aims to provide a technology for more efficiently selecting influencers suitable for advertising. [Means for solving the problem]

[0006] The present invention, which corresponds to one aspect for solving the above-mentioned problem, is a server that communicates with a client terminal, comprising one or more processors, a memory, and a program stored in the memory, wherein the program, when executed by the one or more processors, causes the server to acquire first user information related to a first post of a first influencer, acquire second user information related to a second post of an influencer other than the first influencer, calculate a similarity of followers of the other influencer to followers of the first influencer based on the first user information and the second user information, select a second influencer from the other influencers that is determined to be similar to the first influencer according to the similarity, and notify the client terminal of information about the second influencer. [Effects of the Invention]

[0007] According to the present invention, it is possible to provide a technology for more efficiently selecting influencers suitable for advertising. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing an example of the configuration of a system 10 according to an embodiment. [Figure 2] FIG. 1 is a diagram showing an example of a hardware configuration of an information processing apparatus according to an embodiment. [Figure 3] 6 is a flowchart corresponding to an example of processing executed in the server 101 according to the embodiment. [Figure 4A] 4 is a flowchart corresponding to an example of processing executed between a server 101 and a client terminal 102 according to the embodiment. [Figure 4B] 10 is a flowchart corresponding to an example of a search process executed in the server 101 according to the embodiment. [Figure 5A] FIG. 2 is a diagram showing an example of a display screen of a client terminal 102 according to the embodiment. [Figure 5B] FIG. 10 is a diagram showing another example of the display screen of the client terminal 102 according to the embodiment. [Figure 5C] FIG. 10 is a diagram showing yet another example of the display screen of the client terminal 102 according to the embodiment. [Figure 5D] FIG. 10 is a diagram showing yet another example of the display screen of the client terminal 102 according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, the embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the scope of the invention as claimed, and not all combinations of features described in the embodiments are necessarily essential to the invention. Two or more of the features described in the embodiments may be arbitrarily combined. Furthermore, the same reference numerals are used for the same or similar components, and redundant explanations will be omitted.

[0010] <System configuration> 1 shows a general configuration of a system 10 corresponding to an embodiment. Here, a server 101 which is an information processing device that implements a service corresponding to this embodiment, a client terminal 102 which is an information processing device used by a client that receives information provided by the server 101, and an SNS server 103 which provides information on influencers to the server 101 are connected via a network 104 such as the Internet. An SNS user information database 105 is connected to the server 101, and an SNS information database 106 is connected to the SNS server 103.

[0011] The server 101 is an information processing device that mainly executes processing corresponding to this embodiment. The server 101 collects and acquires information on registered users who are posting information on the SNS server 103 via the network 104 using an API provided by the SNS server 103, and stores the information in the SNS user information database 105. Regarding the information on SNS users to be registered in the SNS user information database 105, only information on SNS users who satisfy certain conditions may be registered. The certain conditions include, for example, that the number of posts on the channel or account of the SNS user is equal to or greater than a predetermined number of posts, that the number of registered followers (also simply referred to as the number of followers) of the channel is equal to or greater than a predetermined number of followers, that the total number of views of the content of the channel is equal to or greater than a predetermined number of views, and that the number of high ratings (so-called "likes") for the content of the channel is equal to or greater than a predetermined number of ratings. The acquired SNS user information may also include information on the followers of the SNS user. The follower information includes, for example, the number of followers, follower IDs, etc. In this embodiment, SNS users registered in the SNS user information database 105 are also referred to as "influencers." Moreover, information about influencers registered in the SNS user information database 105 is collectively referred to as "influencer information."

[0012] The server 101 can also update the information about influencers stored in the SNS user information database 105, for example, periodically.

[0013] The server 101 can also accept the designation of an influencer from the client terminal 102, and based on the influencer information stored in the SNS user information database 105, select (or choose, hereinafter the same) other influencers that are highly similar to the influencer designated by the client, and present a list of influencers to the client terminal 102.

[0014] The client terminal 102 can be configured as any information processing device, such as a general-purpose personal computer or a smartphone. The client terminal 102 transmits information about an influencer designated by the client to the server 101, and receives from the server 101 a list of other influencers that are highly similar to the designated influencer. Although only one client terminal 102 is shown in FIG. 1, this is for illustrative purposes only; multiple client terminals 102 can be connected to the network 104, and multiple different clients can receive information from the server 101 via their respective client terminals 102.

[0015] The SNS server 103 is a server that provides a social networking service (SNS) on the network 104. The SNS information database 106 registers information required for the SNS server 103 to provide the SNS service, including information about users of the SNS (SNS users) (including information about the SNS user's followers (number of followers and follower IDs)). The SNS server 103 also manages information about SNS users, such as videos, comments, and photos posted by SNS users on the SNS service, as well as comments posted by other SNS users in response to those posts and information about users who posted comments (hereinafter referred to as "comment users"). The SNS server 103 provides the server 101 with the information about SNS users contained in the SNS information database 106 via an API.

[0016] In this embodiment, a client using the client terminal 102 sells, for example, products or services within Japan, and advertises on social media and other media to promote the products and services and increase their recognition. The aim is to further increase awareness by having influencers feature the products or services on their own social media accounts or channels. In this embodiment, the types of merchandise that can be advertised are not limited. Any type of product or service can be targeted.

[0017] In addition, other purposes for selecting influencers are also envisioned, such as the following: - To select the destination for placement-based TrueView ads on video streaming sites, which specify the channel to which the ad will be delivered. TrueView ads are ads that are displayed in an interruptive manner while a user is trying to watch a video. - To find influencers who are highly compatible with the target product as interview subjects for a new product monitoring survey. - Enter the PR composition plan (video flow) you are considering and search for influencers that match that composition plan

[0018] When requesting advertising from influencers, the effectiveness of the promotion will vary depending on who is requested, so selecting the influencer is important. While it is possible to request only influencers known to the client, there are limitations, and it is not easy to select influencers who are further suited to advertising from among them.

[0019] In this embodiment, in response to a request from the client terminal 102, the server 101 provides information about other influencers who are highly similar to an influencer specified by the client of the client terminal 102. In this embodiment, when selecting an influencer, attention is paid to the similarity of the influencer's followers and the degree of overlap of users who commented on the influencer's most recent post. Influencers who have followers similar to the followers of the client-specified influencer can be considered to have a high similarity to the client-specified influencer.

[0020] For example, if the majority of followers of influencer A, who is well-known in the cosmetics field, follow influencer B in addition to influencer A, it can be assumed that influencer B is also well-known in the cosmetics field. Therefore, influencer B can be recognized as an influencer with a high degree of similarity to influencer A. Furthermore, the degree of overlap of comment users commenting on an influencer's most recent post is evidence of interest in common users, so users with a high degree of overlap of comment users can be considered to have a high degree of similarity. In this way, other influencers with a high degree of similarity to the influencer specified by the client can be selected based on information about followers.

[0021] In this embodiment, the server 101 selects other influencers (second influencers) that are highly similar to the influencer (first influencer) specified by the client based on the SNS user information managed in the SNS user information database 105, and provides the information to the client terminal 102 as an influencer list.

[0022] 1 illustrates the SNS server 103 as a single server, the embodiment is not limited to this, and multiple different SNS servers 103 may be provided depending on the type and platform of the SNS service. Platforms include a video distribution platform, a still image and video distribution platform, a text message distribution platform, a multimedia distribution platform including still images, video, and text, etc. One platform may include multiple servers and databases.

[0023] <Hardware configuration> Next, the hardware configuration of the server 101 will be described with reference to Fig. 2. The server 101 can be configured as an information processing device, for example, from one or more personal computers. In Fig. 2, a CPU / GPU 201 as one or more processors controls the server 101 using programs and data stored in a RAM (random access memory) 202, a ROM (read only memory) 205, an internal storage device 207, and the like as memories, and executes processing corresponding to the embodiments described below. The RAM 202 has an area for reading processing programs stored in the internal storage device 207 and information stored in the external storage device 208, and also has a work area used by the CPU / GPU 201 when executing various processes.

[0024] The input unit 203 is an input means for receiving input from the administrator of the server 101, and is composed of a keyboard, a mouse, etc. The communication I / F (interface) 204 functions as an I / F for connecting to the network 104, etc. The ROM 205 stores programs (such as a boot program) that control the entire server 101, etc. The display unit 206 is a display unit that serves as a display screen, and is composed of a liquid crystal display device, etc.

[0025] The internal memory device 207 is mainly composed of a hard disk and stores programs and various application data for the server 101 to execute processes. The data stored here is read into the RAM 202 as needed. The external memory device 208 is a database, corresponding to the SNS user information database 105, and various information and the like are stored therein at any time. The bus 209 provides interconnection for each of the above-mentioned blocks.

[0026] Although FIG. 2 has described the hardware configuration of the server 101, the basic hardware configuration of the client terminal 102 and the SNS server 103 can also be made the same as that shown in FIG. 2.

[0027] <Collection of SNS User Information> The processes in the server 101 will be described. FIG. 3 is a flowchart showing an example of the processes in the server 101. The processes corresponding to the flowchart can be realized, for example, by the CPU / GPU 201 of the server 101 executing the corresponding programs (stored in the ROM 205, the internal memory device 207, etc.).

[0028] In S301, the server 101 uses the API of the SNS server 103 to collect and obtain information of predetermined registered users in the services provided by the SNS server 103. The services include, for example, YouTube (registered trademark), Instagram (registered trademark), TikTok (registered trademark), Facebook (registered trademark), X (formerly Twitter (registered trademark)), etc., but are not limited thereto. The information of the registered users includes the profile information of the registrant and the information of other users following the registrant (including the number of followers and the follower user IDs). The information of the registered users further includes information regarding the posts of the registered user, specifically, the posting date and time, information regarding the posting content (post title, summary information, hashtags), and information regarding the comments posted by other SNS users on the post (comment user name, ID, comment posting date and time), etc.

[0029] The method of acquiring information about SNS users is not limited to the above-mentioned method, and may be performed by sending or providing a predetermined questionnaire to SNS users and receiving the responses from the SNS users by the server 101. Alternatively, the SNS users may be interviewed and the responses obtained therefrom may be acquired as SNS user information.

[0030] The SNS users whose information is collected and acquired in S301 may be SNS users who satisfy the following conditions: the number of posts made to a specific SNS is equal to or greater than a specific number of posts, the number of followers is equal to or greater than a specific number of followers, the total number of views of posts is equal to or greater than a specific number of views, the number of likes is equal to or greater than a specific number of ratings, etc. In this embodiment, SNS users who satisfy these conditions and are registered in the SNS user information database 105 are called influencers.

[0031] In the next step S302, information related to the content posted on the SNS by the influencer whose information was acquired in step S301 (for example, post title, summary information, hashtag, comment, etc.), information on the commenting user, etc. is acquired for each SNS service. The commenting user information includes ID information and user name for identifying the commenting user.

[0032] In the following S303, the various pieces of information acquired in S301 and S302 are stored in the SNS user information database 105. The information stored here is collectively referred to as influencer information. In this case, accounts of the same influencer are associated across different SNS services based on mutual link information between accounts across SNS services. For example, in recent years, it has become common for a given influencer to have accounts on YouTube (registered trademark), Instagram (registered trademark), TikTok (registered trademark), Facebook (registered trademark), and X (formerly Twitter (registered trademark)), and each account is managed in association with the same influencer. Therefore, the influencer information for each influencer includes information related to accounts on different SNS services.

[0033] In S304, the information of the SNS user saved in S303 is processed, such as by adding a search index. This is to enable influencers to be searched for by any keyword in the process of FIG. 4A, which will be described later. The above process can be performed periodically for each piece of influencer information.

[0034] <Influencer selection> Next, a method for selecting an influencer will be described. In this embodiment, the server 101 selects a second influencer that is deemed to have a high degree of similarity to a first influencer designated by a client. The first influencer may be a single person or multiple people, and it is preferable that the second influencer be multiple people.

[0035] 4A is a timing chart showing an outline of the flow of processing executed in the system 10 according to this embodiment. This processing can be realized, for example, by the CPU / GPU 201 of each of the server 101 and the client terminal 102 executing a corresponding program (stored in the ROM 205, the internal storage device 207, etc.).

[0036] In S401, the client terminal 102 displays a search screen on the display unit 206. The search screen is provided in advance by the server 101 and displayed. An example of the search screen displayed here is as shown in FIG. 5A. In the following S402, the client terminal 102 accepts an operation input from the client via the input unit 203. The operation input is an input to the screen 500 shown in FIG. 5A.

[0037] 5A shows an example of a search screen for specifying a first influencer and searching for similar influencers. FIG. 5A shows a state in which no information has been entered. In FIG. 5A, screen 500 includes a keyword input area 501, a filter condition setting button 502, a search button 503, a display area 504 for specified candidates, a display area 505 for specified influencers, and a search button 506 for similar influencers.

[0038] Any keyword for identifying the client that the client wishes to designate can be entered in the keyword entry area 501. For example, in the case of beauty, a keyword for identifying a category such as "beauty influencer," "beauty YouTuber," "beauty related," or "beauty specialist" may be entered, or the name or ID of a specific influencer, or any other information for identifying the influencer may be entered.

[0039] When the refinement condition button 502 is selected, the screen shown in FIG. 5B is displayed, and refinement conditions for the influencer to be searched can be set in addition to the keywords. Screen 510 shown in FIG. 5B is an example of a refinement condition input screen. Various refinement conditions can be set in refinement condition 511. Once the refinement condition 511 has been set, the user can return to the original screen 500 by selecting OK button 513 or cancel button 512.

[0040] On screen 510, first, the type of social media for the influencer can be specified. For example, YouTube (registered trademark), Instagram (registered trademark), TikTok (registered trademark), Facebook (registered trademark), X (formerly Twitter (registered trademark)), or any combination thereof can be specified.

[0041] Next, attributes such as gender and age group can be set. The number of followers can also be specified. The field of expertise, number of most recent posts, and number of comments can also be specified. These can be selected from pre-prepared options, or any item can be entered. For "most recent," multiple options can be provided, such as 1 week, 10 days, 2 weeks, 3 weeks, or 1 month. Any other filtering conditions can be entered in the optional input field. If no settings are made for the above setting items, the setting items will not be used as filtering conditions.

[0042] By setting such narrowing conditions, it is possible to limit the search to influencers such as those listed below. Influencers who have posted more than a certain number of times recently, for example, more than 10 times in the last month Influencers with a certain number of followers, more than 50,000 Influencers who have accounts on multiple services, for example, a YouTube account, an X account, and an Instagram account Influencers whose posts related to keyword 501 account for a certain percentage (e.g., 80%) or more of the influencer's posts

[0043] After a keyword is entered in the input field 501 and a filtering condition is set, when the search button 503 is operated, the input information is transmitted from the client terminal 102 to the server 101 in S403. In S404, the server 101 processes the received input information. In this case, since a keyword for searching for influencers has been received, the server 101 searches the SNS user information database 105 based on the received keyword and filtering condition. For example, when a keyword related to "beauty" is specified and female is specified as the attribute, information on registered female influencers related to beauty is extracted.

[0044] The server 101 creates a list of designated candidates by listing the information on the extracted influencers. If the number of designated candidate influencers included in the list exceeds a certain number, the list may include only the designated candidates with the highest number of followers, most recent posts, or most recent comments, for example.

[0045] In the following S405, the list of designated candidates is sent to the client terminal 102 as a processing result. When the client terminal 102 receives the list of designated candidates, in S406, the client terminal 102 updates the display content of the search screen 500. Specifically, the list of designated candidates is displayed in the display area 504 of designated candidates shown in FIG. 5A, resulting in the state shown in FIG. 5C. If there are many candidates, a scroll bar 504A is displayed in the display area 504, allowing the display area to be scrolled.

[0046] In the display state shown in FIG. 5C, the client terminal 102 accepts an operation input from the client. If a keyword is re-input, the above-described processes of S402 to S406 are repeated. On the other hand, if a designated candidate is selected from the list of designated candidates displayed in the display area 504, the designated influencer is displayed in the display area 505. In addition, detailed information about each designated candidate may be acquired from the server 101. For example, when one of the candidates displayed as the designated candidate is selected and an instruction to display detailed information is input (for example, by right-clicking the mouse on the input unit 203 and then selecting "display detailed information," or by double-tapping on the touch panel), the detailed information is transmitted from the server 101 and displayed on the screen. This process can also be included in the above-described processes of S402 to S406.

[0047] When the designation of the first influencer is completed according to the above process and the search button 506 for similar influencers is selected in S407, the client terminal 102 transmits search information to the server 101. The search button 506 can be grayed out until the designated influencer is displayed in the display area 505. The search information includes information that identifies the designated influencer. Note that although one influencer is designated in FIG. 5C, multiple influencers may be designated.

[0048] When the server 101 receives a search instruction for similar influencers from the client terminal 102, the server 101 executes search processing in S409. Details of the search processing will be described later with reference to Fig. 4B. When the search processing is completed, the server 101 transmits the search results to the client terminal 102 in S410.

[0049] Upon receiving the search results, the client terminal 102 displays them in a list in S411. FIG. 5D shows an example of the display of the search results. In FIG. 5D, the inspection result screen 520 displays second influencers determined to be similar to the first influencer specified by the client in individual areas 521, along with the account name, number of views, number of likes, number of comments, etc. The "account name" indicates the name of the account used by the second influencer. The "number of views" indicates the total number of views for a recent fixed period (e.g., one week, two weeks, or one month) or for a certain number of recent posts (e.g., five posts, ten posts, etc.). Alternatively, it may be the average number of views. The "number of likes" indicates the number of likes received for the influencer's posts, and may be the total or average for the period corresponding to the number of views or the number of posts. The "number of comments" indicates the number of comments made on the influencer's post, and may be the total or average value for the period corresponding to the number of views or the number of posts.

[0050] Screen 520 includes a control 522 for displaying detailed information about each influencer. When displaying the search results, influencers determined to be similar are displayed on the screen in descending order of similarity. By operating control 522, the client can check detailed information about each displayed influencer.

[0051] Screen 520 also includes check boxes 523, allowing the user to check the influencers for whom the user wishes to request a consultation or quotation. Check boxes 523 are assigned to individual influencers and a check box for selecting all influencers at once. At the bottom of screen 520, a button 524 for requesting a consultation or quotation and a back button 525 are displayed. Operating the button 524 for requesting a consultation or quotation can send a request to the server 101 for an estimate of the costs involved in placing an advertising request with the influencers whose check boxes are checked. Operating the button 524 for requesting a consultation or quotation in step S417 is considered to have accepted the request for consultation or quotation, and the client terminal 102 sends information requesting quotation, including information about the checked influencers, to the server 101 in step S418. If the user wishes to rerun the search, the user can select the back button 525 to return to the screen of FIG. 5A or 5C.

[0052] When the request information is transmitted, the server 101 creates an estimate in S419 and transmits the estimate to the client terminal 102 in S420. The client terminal 102 displays the received estimate on the display unit 206 in S421.

[0053] The display of the search results in FIG. 5D may include a list of multiple influencers. For example, influencers determined to be similar may be grouped according to the degree of similarity and displayed for each group. The groups may be divided into three groups, for example, high, medium, and low similarity groups. For the group with the highest similarity, the individual influencers included therein may be displayed by default. Also, check boxes 523 may be checkable for each group.

[0054] Next, with reference to Fig. 4B, the details of the search process in S409 in Fig. 4A will be described. First, in S409-1, information about followers of a first influencer, who is an influencer designated by a client, is obtained from the SNS user information database 105. The information about followers includes, for example, the following information. Note that the SNS service (YouTube, Instagram, X, etc.) from which the information is obtained does not matter, but the information is obtained for each SNS service. Follower count information Information about users who commented on the first influencer's post Information on users who liked the first influencer's post

[0055] Here, posts for which user information is acquired refer to at least one of the following posts: a predetermined number of posts; posts made within a predetermined period from the present (e.g., one week, ten days, two weeks, three weeks, one month, or more); a predetermined number of posts with a predetermined number of comments per post (e.g., 100, 200, 500, or more); posts made within a predetermined period from the present with a predetermined number of comments per post (e.g., 100, 200, 500, or more); a predetermined number of posts with a predetermined number of ratings per post (e.g., 100, 200, 500, or more); and posts made within a predetermined period from the present with a predetermined number of ratings per post. Here, a client can specify an SNS service, and in that case, user information is acquired regarding posts on the specified SNS service. For example, if a filtering condition is specified in FIG. 5B, that condition can be referenced.

[0056] In the next step S409-2, influencers to be compared are selected. The selection criteria here may be, for example, at least one of influencers with the same attributes (e.g., gender, age) or field of expertise as the first influencer, influencers with the same or more followers, and influencers with a certain number of recent views or more, or all of these. If a narrowing-down condition is specified in FIG. 5B, that condition may be referenced.

[0057] In the following S409-3, for the influencer to be compared acquired in S409-2, information about followers is acquired from the SNS user information database 105. The information about followers is the same as that described in S409-1.

[0058] In the following S409-4, the information about followers acquired in S409-1 is compared with the information about followers acquired in S409-3 to calculate follower similarity, and the influencer being compared is sorted in order of similarity to determine the second influencer. When comparing information about followers, for example, when comparing comment users, a comparison is made for a common SNS service. For example, when targeting users who posted comments on YouTube videos posted by a first influencer, a comparison is also made for the comparison influencer with users who posted comments on the YouTube videos posted by the comparison influencer. This is because comparing comments posted on different SNS services does not necessarily mean that the comment users use the same account name, and the number of comments also varies depending on the nature of the SNS service.

[0059] The similarity can be calculated by calculating a confidence interval of the population ratio for follower information. Specifically, the similarity between the followers of the first influencer and the followers of the comparison influencer is calculated by calculating a confidence interval of the population ratio for the overlap rate of comment users who posted comments on each post of the first influencer and the comparison influencer. The overlap rate of comment users refers to the proportion of comment users who comment on the posts of the first influencer who also comment on the posts of the comparison influencer.

[0060] Specifically, let Ft be the total number of followers of a first influencer, and Fc be the total number of followers of a comparison influencer. When considering the overlap rate between Ft and Fc, if Ft and Fc could be directly compared, the overlap rate could be obtained. However, if there are tens of thousands, hundreds of thousands, or millions of followers, the calculation load increases accordingly. Therefore, in this embodiment, the overlap rate of comment users who comment on posts by each influencer is calculated, and a confidence interval for the population ratio is calculated based on this to estimate the overlap rate of the number of followers.

[0061] For example, suppose a first influencer has 100,000 followers and a comparison influencer has 80,000 followers. Of these, the number of commenters commenting on posts by both influencers is 1,000 for the first influencer and 800 for the comparison influencer. When calculating the number of commenters for multiple posts, duplicates of the same person are excluded. Suppose the number of duplicate commenters posting comments is 500. In this case, the sample size n is 1,000, the sample proportion p is 0.5 (500 / 1,000), and assuming a confidence level of 95%, ignoring the correction term, the formula for calculating the confidence interval for the population proportion is as follows:

[0062] Lower limit: PRmin = p-1.96 × (p(1-p)) 1 / 2 / (n) 1 / 2 formula 1 Upper limit: PRmax = p + 1.96 × (p(1-p)) 1 / 2 / (n) 1 / 2 formula 2 Applying the above values ​​to this, the lower limit PRmin is calculated as 47% and the upper limit PRmax is calculated as 53%. In this case, it is estimated that the followers of the first influencer will match up to 53% of the followers of the comparison influencer.

[0063] The correction term C is expressed as follows for Equations 1 and 2: C={(Nn) / (N-1)} 1 / 2The lower and upper limits are calculated by multiplying Equation 1 and Equation 2 by the value of the correction term. In the correction term, N represents the population size, and n represents the sample size. In the above case, N is 100,000. A population size N of less than 100,000 is called a finite population, and one that is 100,000 or more or cannot be measured is called an infinite population; the correction term for an infinite population is approximately 1 and can be ignored. In the above example, the population size N was 100,000, so the correction term was ignored.

[0064] Similarly, when calculations are performed for other influencers to be compared using the above formulas 1 and 2, the proportion of followers of each of the influencers to be compared among the followers of the first influencer is estimated.

[0065] The upper or lower limit values ​​of the confidence intervals of the population proportions of the influencers to be compared obtained as described above are compared, and a predetermined number of the influencers to be compared starting from the one with the highest upper limit value can be selected as the second influencers. Alternatively, a predetermined number of the influencers to be compared starting from the one with the highest lower limit value can be selected as the second influencers. Furthermore, for influencers to be compared whose lower limit value or upper limit value is greater than a predetermined lower limit threshold, the second influencer may be identified from the one with the highest upper limit value or lower limit value.

[0066] The above describes the case where a single person is specified as the first influencer, but if multiple people are specified, the same processing can be performed for each person. In this case, if there are overlapping comparison influencers determined as second influencers, the overlaps are eliminated in the processing results. In this case, the overlapping comparison influencers may be displayed higher. For example, if three people are specified as first influencers, the comparison influencer determined as the second influencer by all three people may be ranked higher than the other comparison influencers.

[0067] Although the above describes a case where calculation processing is performed using a first influencer as the reference, similar processing may also be performed using a second influencer as the reference. In this case, the proportion of followers of the first influencer among the followers of other influencers is estimated. The higher this proportion, the higher the degree of similarity between the first influencer and the influencer can be estimated. However, if the number of followers of the influencer being compared is significantly lower than the number of followers of the first influencer, this similarity may not be useful as a reference.

[0068] Note that while Equation 1 and Equation 2 are equations for a reliability of 95%, if the reliability is set to 99%, they will be changed to the following equations. The lower limit is p-2.58×(p(1-p)) 1 / 2 / (n) 1 / 2 formula 3 The upper limit is p+258×(p(1-p)) 1 / 2 / (n) 1 / 2 formula 4 If we use Equation 3 and Equation 4 to estimate the population ratio in the above example, the lower limit is 46% and the upper limit is 54%. Again, the calculation ignores the correction term.

[0069] Furthermore, when the sample size n is less than 30, it is possible to apply formulas other than the above formulas 1 to 4. For example, when the number of comments is small, the following formula may be applied for calculation. When the sample size is n and the sample proportion is p, and n<30, The lower limit is n2 / (n1F n +n2) Equation 5 The upper limit is m1F m / (m1F m +m2) Equation 6 In addition, n1=2n(1-p)+2, n2=2np, m1=2np+2, m2=2n(1-p) F n = the horizontal axis value of the upper probability a / 2% of the F distribution with degrees of freedom n1 and n2, F m = the horizontal axis value of the upper probability a / 2% of the F distribution with degrees of freedom m1 and m2 However, a = 0.05 at 95% confidence and a = 0.01 at 99% confidence. The value F on the horizontal axis n For example, this can be calculated using the Excel function FINV as FINV(a / 2, n1, n2).

[0070] In the above, we estimated the similarity of an influencer's followers based on the overlap rate of comment users who posted comments, but using a similar method, we can also estimate the similarity of an influencer's followers based on the overlap rate of users who gave high ratings to a post by a first influencer.

[0071] In the present embodiment described above, by determining the similarity of followers, it is possible to select influencers similar to an influencer designated by a client. In this case, the processing load can be reduced regardless of the number of followers of the influencer. Furthermore, according to this embodiment, once one influencer is designated, the server 101 selects and presents other influencers with similar followers without the client having to manually select them, thereby improving the accuracy of influencer selection. As a result, by simply finding an influencer suitable for a product, the client can easily obtain a comprehensive list of other influencers likely to be suitable for advertising and promotion, allowing the client to thoroughly narrow down the candidates with a limited amount of work.

[0072] Furthermore, according to this embodiment, it is possible to select influencers with a high degree of commonality among followers as the recipients of advertising requests, so that it is possible to approach the same followers via multiple different influencers to advertise products and services, thereby increasing the effectiveness of advertising.

[0073] <Summary of the embodiment> The above-described embodiment discloses at least the following information processing device and computer program. (1) A server that communicates with a client terminal, the server comprising one or more processors, a memory, and a program stored in the memory, the program being executed by the one or more processors to cause the server to: Obtaining first user information regarding a first post of a first influencer; Obtaining second user information regarding a second post of an influencer other than the first influencer; Calculating a similarity between the followers of the other influencer and the followers of the first influencer based on the first user information and the second user information; selecting a second influencer determined to be similar to the first influencer from among the other influencers according to the degree of similarity; notifying the client terminal of information about the second influencer; The server that runs the (2) the first user information is information about a user who posted a comment on the first post; The server according to (1), wherein the second user information is information about a user who posted a comment on the second post. (3) the first user information is information about a user who gave a high rating to the first post; The server according to (1), wherein the second user information is information about a user who gave a high rating to the second post. (4) A server described in any one of (1) to (3), wherein the first post and the second post are at least one of a predetermined number of posts, posts made within a predetermined period from the present, a predetermined number of posts with a number of comments per post equal to or greater than a predetermined number of comments, posts made within a predetermined period from the present with a number of comments per post equal to or greater than a predetermined number of comments, a predetermined number of posts with a number of ratings per post equal to or greater than a predetermined number of ratings, and posts made within a predetermined period from the present with a number of ratings per post equal to or greater than a predetermined number of ratings. (5) The server according to (4), wherein the first user information and the second user information are obtained for each social networking service on which the first post and the second post were made, and the similarity is calculated for each social networking service. (6) The server according to (5), wherein the social networking service on which the first post and the second post were made is a social networking service designated by the client terminal. (7) Calculating the similarity Calculating a first ratio of the number of users common to the first user information and the second user information to the number of first users included in the first user information; The server according to any one of (4) to (6), further comprising: calculating the similarity using a confidence interval of a population ratio based on the first number of users and the first ratio. (8) In calculating the similarity, the first number of users is a sample number n, the first ratio is a sample ratio p, and the lower and upper limits of a confidence interval of the population ratio are calculated as follows: Lower limit: p-1.96×(p(1-p)) 1 / 2 / (n) 1 / 2 Upper limit: p + 1.96 × (p(1-p)) 1 / 2 / (n) 1 / 2 The server according to (7) calculates the number of times ... (9) Selecting the second influencer: The server according to (8), further comprising selecting the second influencer by comparing at least one of the calculated upper limit value and the calculated lower limit value. (10) The server according to (9), wherein the selection of the second influencer is performed by selecting an influencer for which at least one of the calculated upper limit value and the calculated lower limit value is greater than a predetermined threshold value. (11) The server according to (10), wherein the first influencer is designated in the client terminal and notified to the server. (12) A server described in any one of (1) to (11), wherein the first influencer and the other influencers are registered users of a specified social networking service who disseminate information on the specified social networking service and whose number of followers, posts, views, and likes exceeds a specified number. (13) The program, when executed by the one or more processors, causes the server to: Accepting a predetermined request specifying the notified second influencer. The server according to any one of (1) to (12), further executing: (14) A program according to any one of (1) to (13).

[0074] [Other embodiments] The invention is not limited to the above-described embodiments, and various modifications and variations are possible within the spirit and scope of the invention. Therefore, the following claims are appended to clarify the scope of the invention. The information processing device according to the present invention can also be realized by a computer program that causes one or more computers to function as the information processing device. The computer program can be provided / distributed by being recorded on a computer-readable recording medium or via a telecommunications line. [Explanation of symbols]

[0075] 10: System, 101: Server, 102: Client terminal, 103: SNS server, 104: Network

Claims

1. A server that communicates with a client terminal, the server comprising one or more processors, a memory, and a program stored in the memory, the program, when executed by the one or more processors, causing the server to: Obtaining first user information related to a first post of a first influencer; Obtaining second user information regarding a second post of an influencer other than the first influencer; Calculating a similarity between followers of the other influencer and followers of the first influencer based on the first user information and the second user information; selecting a second influencer determined to be similar to the first influencer from among the other influencers according to the degree of similarity; notifying the client terminal of information about the second influencer; The server that runs the

2. the first user information is information of a user who posted a comment on the first post, The server according to claim 1 , wherein the second user information is information about a user who posted a comment on the second post.

3. the first user information is information about a user who has given a high rating to the first post, The server according to claim 1 , wherein the second user information is information about a user who has given a high rating to the second post.

4. The server of claim 1, wherein the first post and the second post are at least one of a predetermined number of posts, posts made within a predetermined period from the present, a predetermined number of posts with a number of comments per post equal to or greater than a predetermined number of comments, posts made within a predetermined period from the present with a number of comments per post equal to or greater than a predetermined number of comments, a predetermined number of posts with a number of ratings per post equal to or greater than a predetermined number of ratings, and posts made within a predetermined period from the present with a number of ratings per post equal to or greater than a predetermined number of ratings.

5. 5. The server according to claim 4, wherein the first user information and the second user information are obtained for each social networking service on which the first post and the second post were made, and the similarity is calculated for each social networking service.

6. The server according to claim 5 , wherein the social networking service on which the first post and the second post were made is a social networking service designated by the client terminal.

7. Calculating the similarity calculating a first ratio of the number of users common to the first user information and the second user information to the number of first users included in the first user information; calculating the similarity using a confidence interval of a population ratio based on the first number of users and the first ratio; The server of claim 6, comprising:

8. In calculating the similarity, the first number of users is a sample number n, the first ratio is a sample ratio p, and the lower and upper limits of a confidence interval of the population ratio are calculated as follows: Lower limit: p-1.96 x (p(1-p)) 1 / 2 / (n) 1 / 2 Upper limit: p + 1.96 × (p (1 − p)) 1 / 2 / (n) 1 / 2 The server according to claim 7, wherein the calculation is based on the following:

9. Selecting the second influencer includes: The server according to claim 8 , further comprising: selecting the second influencer by comparing at least one of the calculated upper limit value and the calculated lower limit value.

10. The server according to claim 9 , wherein the selection of the second influencer is performed by selecting influencers for which at least one of the calculated upper limit value and the calculated lower limit value is greater than a predetermined threshold value.

11. The server of claim 10 , wherein the first influencer is designated in the client terminal and notified to the server.

12. The server of claim 1, wherein the first influencer and the other influencers are registered users of a specified social networking service who disseminate information on the specified social networking service and whose number of followers, posts, views, and likes exceeds a specified number.

13. The program, when executed by the one or more processors, causes the server to: Accepting a predetermined request specifying the notified second influencer. The server according to claim 1 , further comprising:

14. The program according to any one of claims 1 to 13.

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