Information processing device, information processing method, and information processing program

Abstract

To provide content for encouraging users to post comments.SOLUTION: An information processing device comprises a selection unit and a proposal unit. The selection unit selects a user to whom a proposal for posting a comment on other distributed content is to be made on the basis of information about distributed content to which a comment has been posted and information about a user who posted the comment. The proposal unit proposes posting of a comment on other distributed content via content including the distributed content, the comment, and a proposal for posting a comment on the other distributed content to the selected user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] A technology is disclosed that easily realizes review requests by receiving content information and a request to review the content, displaying a message based on the content information on a timeline, and when it is received that a review has been completed for content obtained based on the content information, displaying that fact on the timeline. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-072292 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above-mentioned conventional technology only requests other users who belong to the same group as the user to review content shared in the group, and therefore does not encourage users to post comments on content that is not shared in the group.

[0005] The present application has been made in view of the above, and aims to provide content that encourages users to post comments. [Means for solving the problem]

[0006] The information processing device of the present application is characterized by comprising: a selection unit that selects a user to whom a comment posting for other distributed content is to be suggested based on information about the distributed content to which the comment was posted and information about the poster who posted the comment; and a suggestion unit that suggests to the suggested user that they post a comment for the other distributed content via content that includes the distributed content, the comment, and a suggestion for posting a comment for the other distributed content. [Effects of the Invention]

[0007] According to one aspect of the embodiment, content can be provided to encourage users to post comments. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is an explanatory diagram illustrating an example of information processing according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the configuration of an information processing system according to the embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of the configuration of a terminal device according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of the configuration of the information processing device according to the embodiment. [Figure 5] FIG. 5 is a diagram illustrating an example of the user information database. [Figure 6] FIG. 6 is a diagram illustrating an example of the history information database. [Figure 7] FIG. 7 is a diagram showing an example of a shared chain content. [Figure 8] FIG. 8 is a flowchart showing a processing procedure according to the embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of a hardware configuration. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an information processing device, an information processing method, and an information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited to these embodiments. Furthermore, the same components in the following embodiments will be denoted by the same reference numerals, and duplicated descriptions will be omitted.

[0010] [1. An example of information processing] First, an example of information processing according to the embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of information processing according to the embodiment, which is executed by an information processing device 100. Note that Fig. 1 will be described taking as an example a case where a user is suggested to post a comment on distributed content such as news.

[0011] 1 is an information processing device that is connected to terminal devices 10a and 10b of multiple users Ua and Ub via a network N (see FIG. 2) so that they can communicate with each other via wired or wireless means, and provides various types of information to users Ua and Ub, and is realized, for example, by one or more servers or cloud systems. Hereinafter, users Ua, Ub, ... may be referred to as user U, and terminal devices 10a, 10b, ... may be referred to as terminal devices 10. Furthermore, posted comments may be referred to as comments.

[0012] The terminal device 10 is a smart device such as a smartphone or tablet terminal used by a user U, and is a portable terminal device capable of communicating with any server device via a wireless communication network such as 4G (4th Generation) or LTE (Long Term Evolution). The terminal device 10 has a screen such as a liquid crystal display with a touch panel function, and accepts various operations on displayed data such as content, such as tapping, sliding, and scrolling, performed by the user U with a finger or a stylus. An operation performed on an area of ​​the screen where content is displayed may be considered an operation on the content. The terminal device 10 may be not only a smart device, but also an information processing device such as a desktop PC (Personal Computer) or a notebook PC.

[0013] The information processing device 100 is an information processing device that works in conjunction with the terminal device 10 of each user U and provides API (Application Programming Interface) services for various applications (hereinafter referred to as apps) and various data to the terminal device 10 of each user U, and is realized by a computer, a cloud system, etc.

[0014] Furthermore, the information processing device 100 may be an information processing device that provides some kind of online web service to the terminal device 10 of each user U. For example, the information processing device 100 may provide, as web services, services such as internet connection, search services, SNS (Social Networking Service), electronic commerce (EC), electronic payment, online games, online banking, online trading, hotel and ticket reservations, video and music distribution, news, maps, route searches, route guidance, line information, operation information, and weather forecasts. In practice, the information processing device 100 may cooperate with various servers that provide the above-mentioned web services and act as an intermediary for the web services or may be responsible for processing the web services.

[0015] The information processing device 100 can acquire user information about the user U. For example, the information processing device 100 acquires information about the attributes of the user U, such as the gender, age, and residential area of ​​the user U. The information processing device 100 then stores and manages the information about the attributes of the user U together with identification information (such as a user ID) indicating the user U.

[0016] The information processing device 100 also acquires various types of history information (log data) indicating the behavior of the user U from the terminal device 10 of the user U or from various servers based on the user ID or the like. For example, the information processing device 100 acquires a location history, which is a history of the user U's location and date and time, from the terminal device 10. The information processing device 100 also acquires a search history, which is a history of search queries entered by the user U, from a search server (search engine). The information processing device 100 also acquires a browsing history, which is a history of content viewed by the user U, from a content server. The information processing device 100 also acquires a purchase history (payment history), which is a history of product purchases and payment processes by the user U, from an e-commerce server or a payment processing server. The information processing device 100 may also acquire a listing history and a sales history, which are a history of the user U's listings on the marketplace, from the e-commerce server or the payment processing server. The information processing device 100 also acquires a posting history, which is a history of the user U's postings, from a posting server or SNS server that provides a word-of-mouth posting service. The various servers and the like described above may be the information processing device 100 itself. That is, the information processing device 100 may function as the various servers and the like described above.

[0017] [1-1. Acquiring posted comments] As shown in FIG. 1, first, the information processing device 100 acquires a posted comment a linked to a distributed content a (step S1). The distributed content is, for example, a news article, but may also be a blog article, content posted on a social networking site, or other content. The posted comment is, for example, a comment posted by a poster on the distributed content, or a comment posted by a poster on a comment on the distributed content. The posted comment is the poster's opinion or impression, and includes a character string, a stamp, an emoticon, and the like. Note that the posted comment may be, instead of or in addition to a comment, a URL (Uniform Resource Locator) of another content, or the like.

[0018] The user Ua can post a comment on the distribution content from the terminal device 10a by operating the terminal device 10a. For example, the user Ua operates the terminal device 10a to select a desired distribution content a from a list of distribution contents, and the terminal device 10a associates the comment a created for the distribution content a with the distribution content a and transmits the comment a to the information processing device 100.

[0019] The information processing device 100 can accept comments posted by multiple contributors, including the user Ua, in relation to the distributed content, and store the accepted posted comments in a database. For example, the information processing device 100 has a database in which multiple posted comments are linked to each distributed content, and can acquire multiple posted comments linked to the distributed content from the database or external storage. Contributors of the posted comments include the user Ua.

[0020] [1-2. Acquisition of user information] Next, the information processing device 100 acquires user information (attribute information, history information, etc.) about the user Ua directly or indirectly (via another server device, etc.) from the terminal device 10a of the user Ua (step S2).

[0021] [1-3. Selecting users to whom you would like to suggest a comment post] Next, the information processing device 100 estimates the user attributes of the user to whom a comment posting to other distribution content is proposed based on information about the distribution content a and user information about the comment poster, user Ua, and selects user Ub with the estimated user attributes (step S3). Information about the distribution content includes, for example, the title and content of the distribution content, such as news (it may also be the distributor, theme, or category). User attributes include user segments, user personas, etc.

[0022] In this case, the information processing device 100 may use machine learning to estimate the user attributes of the user to whom a comment posting for another piece of distribution content is proposed, based on the title and content of the distribution content such as news and the user information of the comment poster. For example, the information processing device 100 uses the title and content of the distribution content such as news and the user information of the comment poster as input data, and generates an estimation model that outputs the user attributes of the user to whom a comment posting for another piece of distribution content is proposed. Note that multiple user attributes may be output.

[0023] Alternatively, the information processing device 100 may use machine learning to estimate the user attributes of a user to whom a comment posting for other distributed content is proposed from the title and content of distributed content such as news and the user information of the comment poster. The information processing device 100 may use machine learning to generate an estimation model that uses as input data a set of the title and content of the distributed content, the user information of the comment poster, and the user attributes of a user to whom a comment posting for other distributed content is proposed, and outputs a share score (or a share level). The share score is a score that indicates the degree of association between information about the distributed content to which the comment was posted and the user information of the comment poster, and the user attributes of a user to whom a comment posting for other distributed content is proposed.

[0024] The information processing device 100 may, for example, use image recognition and natural language processing (NLP) to vectorize the title and content of the distribution content, the user information of the comment poster, and the user attributes of the user to whom the comment posting of other distribution content is suggested, and calculate the share score using the cosine similarity of each vector.

[0025] The information processing device 100 may use machine learning to generate an estimation model that uses a set of the title and content of the distribution content, the user information of the comment poster, and a share score as input data, and outputs the user attributes of a user to whom a comment post on other distribution content is proposed or a user with the user attributes. The information processing device 100 inputs a predetermined share score into the estimation model, and acquires, for example, the user attributes of a user to whom a comment post on other distribution content is proposed, or a user with the user attributes, who is not connected to the content of the distribution content based on the behavioral history of user U.

[0026] The machine learning method may be deep learning, a recurrent neural network (RNN), a long short-term memory (LSTM), etc. Note that these are merely examples and are not intended to be limiting.

[0027] The information processing device 100 selects the user Ub from users with user attributes having a predetermined share score, for example. Alternatively, the information processing device 100 may present a plurality of users with user attributes having a predetermined share score as candidates to the user Ua, and allow the user Ua to select the user Ub.

[0028] [1-4. Suggest a comment] Next, the information processing device 100 transmits the previously posted distributed content a and posted comment a to the selected user Ub, and suggests posting a comment on the other distributed content (step S4). For the other distributed content, for example, user Ua may set a new theme for user Ub, such as "What do you think? Tell me about your article on XX," or the selected user Ub may set a new theme based on the previously posted distributed content a and posted comment a and select other distributed content. The previously posted distributed content and posted comment may be multiple in a series of shares. For example, the information processing device 100 suggests posting a comment on the other distributed content via content including the distributed content, the comment, and a suggestion to post a comment on the other distributed content.

[0029] [1-5. Acquiring comments posted on other distributed content] Next, the information processing device 100 acquires posted comment b linked to other distributed content b (step S5). The other distributed content is, for example, the content of a news article, but may also be the content of a blog article, content posted on a social networking site, or other content. The posted comment is, for example, a comment posted by a poster on distributed content, or a comment posted by a poster on a comment on distributed content. The comment is the poster's opinion or impression, and includes a character string, a stamp, an emoticon, etc. Note that the posted comment may be, instead of or in addition to, a URL of other content, etc.

[0030] The user Ub can post a comment on the distribution content from the terminal device 10b by operating the terminal device 10b. For example, the user Ub operates the terminal device 10b to select a desired distribution content b from a list of distribution contents, and the terminal device 10b associates the comment b created for the distribution content b with the distribution content b and transmits the comment b to the information processing device 100.

[0031] When the information processing device 100 receives a comment b posted by the user Ub in association with the distribution content b, the information processing device 100 can store the received posted comment b in a database.

[0032] [1-6. Generating flow points with an overview of share trends] The information processing device 100 repeats the above process, and when a certain number of shares have been made, generates a flow of points that provide an overview of the sharing trends, consisting of the posted comments linked to the distribution content and the posted comments linked to other distribution content, based on the shared distribution content and the content of the posted comments (step S6). The information processing device 100 inputs, for example, the shared distribution content, the content of the posted comments thereto, and a prompt including a sentence or the like that specifies the generation of a flow of points that provide an overview of the sharing trends, into a generative model, and obtains a flow of points that provide an overview of the sharing trends. The generative model may be, for example, a GPT (Generative Pretrained Transformer) model.

[0033] The information processing device 100 then creates a list of the shared users, the distribution content, its theme, and the posted comments, and generates a share chain content (sometimes referred to as chain content) that includes a share chain consisting of posted comments linked to the distribution content and posted comments linked to other distribution content, as well as flow points that provide an overview of the sharing trends, and provides this to the user U.

[0034] [1-7. Variation] The information processing device 100 may extract requests such as "What do you think? Tell me about your article on XX" from the posted comments, determine the user attributes of the user to whom the suggestion is to be made or a user U with those user attributes from the extracted requests, and make a suggestion to encourage the user U determined to be the suggestion recipient to post a comment in accordance with the request. At this time, the information processing device 100 may estimate the user attributes (which may be a user segment or a user persona) based on the extracted requests. Furthermore, the information processing device 100 may also subtly prompt a user U with the user attributes of the user to whom the suggestion is to be made, such as "What do you think? Tell me about your article on XX," to encourage the user U to post.

[0035] In addition, the information processing device 100 may generate share chain content that includes the distribution content that the user U wants to view, a share chain between the distribution content and the user, and flow points that provide an overview of the sharing trends, and provide this to the user U.

[0036] In addition, the information processing device 100 may generate and provide to the user U share chain content that includes a share chain between distribution content and users, including posters that the user U wants to view, and flow points that provide an overview of share trends.

[0037] In this way, the information processing device 100 selects a user to whom a comment posting for another distributed content is to be suggested based on information about the distributed content to which the comment was posted and information about the poster who posted the comment, and suggests to the suggested user that the user post a comment for the other distributed content. In this way, the information processing device 100 allows a plurality of users U to share the distributed content, thereby creating casual connections between the users U. Furthermore, once a certain number of shares have been shared, the information processing device 100 generates flow points that provide an overview of sharing trends from the content of the shares and the content of the posted comments, and can provide share chain content that visualizes, together with the flow points, a share chain consisting of posted comments linked to the distributed content and posted comments linked to other distributed content.

[0038] [2. Example of information processing system configuration] Next, the configuration of an information processing system 1 including an information processing device 100 according to an embodiment will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration of the information processing system 1 according to an embodiment. As shown in Fig. 2, the information processing system 1 according to an embodiment includes a terminal device 10 and an information processing device 100. These various devices are connected to each other via a network N so as to be able to communicate with each other via a wired or wireless connection. The network N is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network) such as the Internet.

[0039] Furthermore, the number of devices included in the information processing system 1 shown in Fig. 2 is not limited to that shown in the figure. For example, in Fig. 2, for the sake of simplicity, only two terminal devices 10 are shown, but this is merely an example and is not limiting, and three or more devices may be included.

[0040] The terminal device 10 is an information processing device used by a user U. For example, the terminal device 10 may be a smart device such as a smartphone or a tablet terminal, a feature phone, a PC (Personal Computer), a PDA (Personal Digital Assistant), a game console or AV device with a communication function, a car navigation system, a wearable device such as a smart watch or a head-mounted display, smart glasses, etc. The terminal device 10 may also be a house / building, a car, a home appliance, an electronic device, etc. that is compatible with the Internet of Things (IOT).

[0041] In addition, the terminal device 10 can connect to a network N via a wireless communication network such as LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation: 5th generation mobile communication system), or via short-range wireless communication such as Bluetooth (registered trademark) or wireless LAN (Local Area Network), and communicate with the information processing device 100.

[0042] The information processing device 100 is, for example, a computer such as a PC or a blade server, or a mainframe or a workstation, etc. The information processing device 100 may be realized by cloud computing.

[0043] [3. Example of terminal device configuration] Next, the configuration of the terminal device 10 will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the configuration of the terminal device 10. As shown in Fig. 3, the terminal device 10 includes a communication unit 11, a display unit 12, an input unit 13, a positioning unit 14, a sensor unit 20, a control unit 30 (controller), and a storage unit 40.

[0044] (Communications Department 11) The communication unit 11 is connected to a network N (see FIG. 2) by wire or wirelessly, and transmits and receives information to and from the information processing device 100 via the network N. For example, the communication unit 11 is realized by a NIC (Network Interface Card), an antenna, etc.

[0045] (Display section 12) Display unit 12 is a display device that displays various information such as position information. For example, display unit 12 is a liquid crystal display (LCD) or an organic electro-luminescent display (OLED). Display unit 12 is also a touch panel display, but is not limited to this.

[0046] (Input section 13) The input unit 13 is an input device that accepts various operations from the user U. For example, the input unit 13 has buttons for inputting characters, numbers, and the like. The input unit 13 may be an input / output port (I / O port), a USB (Universal Serial Bus) port, or the like. If the display unit 12 is a touch panel display, a part of the display unit 12 functions as the input unit 13. The input unit 13 may be a microphone that accepts voice input from the user U. The microphone may be wireless.

[0047] (Positioning unit 14) The positioning unit 14 receives signals (radio waves) transmitted from satellites of a GPS (Global Positioning System), and acquires position information (e.g., latitude and longitude) indicating the current position of the terminal device 10, which is the device itself, based on the received signals. That is, the positioning unit 14 positions the position of the terminal device 10. Note that GPS is merely an example of a GNSS (Global Navigation Satellite System).

[0048] The positioning unit 14 can also measure the position using various methods other than GPS. For example, the positioning unit 14 may measure the position by using various communication functions of the terminal device 10 as an auxiliary positioning means for position correction, etc., as described below.

[0049] (Wi-Fi positioning) For example, the positioning unit 14 uses a Wi-Fi (registered trademark) communication function of the terminal device 10 or a communication network provided by each communication company to measure the position of the terminal device 10. Specifically, the positioning unit 14 performs Wi-Fi communication or the like and measures the distance to a nearby base station or access point, thereby measuring the position of the terminal device 10.

[0050] (Beacon positioning) The positioning unit 14 may also measure the position by using a Bluetooth (registered trademark) function of the terminal device 10. For example, the positioning unit 14 measures the position of the terminal device 10 by connecting to a beacon transmitter connected by the Bluetooth (registered trademark) function.

[0051] (geomagnetic positioning) The positioning unit 14 also measures the position of the terminal device 10 based on a geomagnetic pattern of a structure that has been measured in advance and a geomagnetic sensor that the terminal device 10 has.

[0052] (RFID positioning) Furthermore, for example, if the terminal device 10 has a function of an RFID (Radio Frequency Identification) tag equivalent to a contactless IC card used at station ticket gates, in stores, etc., or has a function of reading an RFID tag, the location where the terminal device 10 was used is recorded together with information on the payment or the like made by the terminal device 10. The positioning unit 14 may obtain such information to determine the location of the terminal device 10. Alternatively, the location may be determined by an optical sensor, an infrared sensor, or the like provided in the terminal device 10.

[0053] The positioning unit 14 may measure the position of the terminal device 10 using one or a combination of the above-mentioned positioning means, as needed.

[0054] (Sensor unit 20) The sensor unit 20 includes various sensors mounted on or connected to the terminal device 10. The connection may be wired or wireless. For example, the sensors may be detection devices other than the terminal device 10, such as wearable devices or wireless devices. In the example shown in FIG. 3 , the sensor unit 20 includes an acceleration sensor 21, a gyro sensor 22, a barometric pressure sensor 23, a temperature sensor 24, a sound sensor 25, a light sensor 26, a magnetic sensor 27, and an image sensor (camera) 28.

[0055] The above-described sensors 21 to 28 are merely examples and are not intended to be limiting. That is, the sensor unit 20 may be configured to include some of the sensors 21 to 28, or may include other sensors such as a humidity sensor in addition to or instead of the sensors 21 to 28.

[0056] The acceleration sensor 21 is, for example, a three-axis acceleration sensor, and detects physical movements of the terminal device 10, such as the direction of movement, speed, and acceleration of the terminal device 10. The gyro sensor 22 detects physical movements of the terminal device 10, such as tilt in three axial directions, based on the angular velocity of the terminal device 10. The air pressure sensor 23 detects, for example, the air pressure around the terminal device 10.

[0057] Since the terminal device 10 includes the acceleration sensor 21, the gyro sensor 22, the atmospheric pressure sensor 23, etc., it is possible to measure the position of the terminal device 10 using a technique such as Pedestrian Dead-Reckoning (PDR) that uses these sensors 21 to 23. This makes it possible to obtain indoor position information that is difficult to obtain using a positioning system such as GPS.

[0058] For example, the number of steps, walking speed, and distance walked can be calculated using a pedometer that uses the acceleration sensor 21. In addition, the direction of travel, line of sight, and body tilt of the user U can be determined using the gyro sensor 22. In addition, the altitude and floor on which the user U's terminal device 10 is located can be determined from the air pressure detected by the air pressure sensor 23.

[0059] The temperature sensor 24 detects, for example, the temperature around the terminal device 10. The sound sensor 25 detects, for example, the sound around the terminal device 10. The light sensor 26 detects the illuminance around the terminal device 10. The magnetic sensor 27 detects, for example, the geomagnetism around the terminal device 10. The image sensor 28 captures an image around the terminal device 10.

[0060] The above-mentioned air pressure sensor 23, temperature sensor 24, sound sensor 25, light sensor 26, and image sensor 28 can detect the air pressure, temperature, sound, and illuminance, respectively, and capture images of the surroundings, thereby detecting the environment and situation around the terminal device 10. Furthermore, the accuracy of the location information of the terminal device 10 can be improved based on the environment and situation around the terminal device 10.

[0061] (control unit 30) The control unit 30 includes, for example, a microcomputer having a CPU (Central Processing Unit), ROM (Read Only Memory), RAM, input / output ports, etc., and various other circuits. The control unit 30 may also be configured with hardware such as an integrated circuit, for example, an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 30 includes a transmitting unit 31, a receiving unit 32, and a processing unit 33.

[0062] (Transmitter 31) The transmission unit 31 can transmit, for example, various information input by the user U using the input unit 13, various information detected by each sensor 21 to 28 mounted on or connected to the terminal device 10, and location information of the terminal device 10 measured by the positioning unit 14 to the information processing device 100 via the communication unit 11.

[0063] (Receiving unit 32) The receiving unit 32 can receive various information provided by the information processing device 100 and requests for various information from the information processing device 100 via the communication unit 11.

[0064] (Processing unit 33) The processing unit 33 controls the entire terminal device 10, including the display unit 12. For example, the processing unit 33 can output various information transmitted by the transmission unit 31 and various information received from the information processing device 100 by the reception unit 32 to the display unit 12 for display.

[0065] (Storage unit 40) The storage unit 40 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 an HDD (Hard Disk Drive), an SSD (Solid State Drive), an optical disk, etc. The storage unit 40 stores various programs, various data, etc.

[0066] [4. Configuration example of information processing device] Next, the configuration of the information processing device 100 according to the embodiment will be described with reference to Fig. 4. Fig. 4 is a diagram showing an example of the configuration of the information processing device 100 according to the embodiment. As shown in Fig. 4, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

[0067] (Communication unit 110) The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is also connected to a network N (see FIG. 2) by wire or wirelessly.

[0068] (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 an HDD, an SSD, an optical disk, etc. As shown in FIG. 4 , the storage unit 120 has a user information database 121 and a history information database 122.

[0069] (User Information Database 121) The user information database 121 stores user information about the user U. For example, the user information database 121 stores various information such as the attributes of the user U. FIG. 5 is a diagram showing an example of the user information database 121. In the example shown in FIG. 5, the user information database 121 has items such as "User ID (Identifier)," "Age," "Gender," "Home," "Workplace," and "Interests."

[0070] The "user ID" indicates identification information for identifying the user U. The "user ID" may be the contact information of the user U (telephone number, email address, etc.), or may be identification information for identifying the terminal device 10 of the user U.

[0071] Furthermore, "age" indicates the age of user U identified by the user ID. Note that "age" may be information indicating the specific age of user U (e.g., 35 years old), or may be information indicating the generation of user U (e.g., 30s). Alternatively, "age" may be information indicating the date of birth of user U, or may be information indicating the generation of user U (e.g., born in the 1980s). Furthermore, "gender" indicates the gender of user U identified by the user ID.

[0072] Furthermore, "home" indicates the location information of the home of user U identified by the user ID. In the example shown in FIG. 5, "home" is illustrated as an abstract code such as "LC11," but it may also be latitude and longitude information, etc. Furthermore, for example, "home" may also be the name of an area or an address.

[0073] Furthermore, "workplace" indicates location information of the workplace (school in the case of a student) of user U identified by the user ID. In the example shown in FIG. 5, "workplace" is illustrated as an abstract code such as "LC12," but it may also be latitude and longitude information, etc. Furthermore, for example, "workplace" may also be the name of a region or an address.

[0074] Furthermore, "interests" indicate the interests of a user U identified by a user ID. In other words, "interests" indicate subjects in which a user U identified by a user ID is highly interested. For example, "interests" may be search queries (keywords) entered by a user U into a search engine. Note that, in the example shown in FIG. 5, one "interest" is illustrated for each user U, but there may be multiple "interests."

[0075] For example, in the example shown in FIG. 5, the age of user U identified by user ID "U1" is "20s" and the gender is "male." Furthermore, for example, the home address of user U identified by user ID "U1" is "LC11." Furthermore, for example, the workplace of user U identified by user ID "U1" is "LC12." Furthermore, for example, the user U identified by user ID "U1" is interested in "sports."

[0076] 5, abstract values ​​such as "U1", "LC11", and "LC12" are used for illustration, but "U1", "LC11", and "LC12" are assumed to store information such as specific character strings and numerical values. Below, abstract values ​​may also be illustrated in diagrams relating to other information.

[0077] The user information database 121 is not limited to the above, and may store various types of information depending on the purpose. For example, the user information database 121 may store various types of information related to the terminal device 10 of the user U. The user information database 121 may also store information related to the user U's attributes, such as demographic attributes, psychographic attributes, geographic attributes, and behavioral attributes. For example, the user information database 121 may store information such as name, family structure, hometown (hometown), occupation, job title, income, qualifications, type of residence (detached house, apartment, etc.), whether or not the user has a car, commuting time, commuting route, commuter pass section (station, line, etc.), frequently used stations (other than the nearest station to home or workplace), extracurricular activities (location, time zone, etc.), hobbies, interests, lifestyle, etc.

[0078] (History Information Database 122) The history information database 122 stores various information related to history information (log data) that indicates the behavior of the user U. Fig. 6 is a diagram showing an example of the history information database 122. In the example shown in Fig. 6, the history information database 122 has items such as "user ID," "location history," "search history," "browsing history," "purchase history," and "posting history."

[0079] "User ID" indicates identification information for identifying user U. "Location history" indicates location history, which is a history of user U's locations and movements. "Search history" indicates search history, which is a history of search queries entered by user U. "Browsing history" indicates browsing history, which is a history of content viewed by user U. "Purchase history" indicates purchase history, which is a history of purchases made by user U. "Posting history" indicates posting history, which is a history of posts made by user U.

[0080] For example, in the example shown in Figure 6, user U, identified by user ID "U1," moved as shown in "Location History #1," searched as shown in "Search History #1," viewed content as shown in "Viewing History #1," purchased specific products at specific stores as shown in "Purchase History #1," and posted as shown in "Posting History #1."

[0081] Here, in the example shown in Figure 6, abstract values ​​such as "U1", "Location History #1", "Search History #1", "Browsing History #1", "Purchase History #1", and "Post History #1" are used for the illustration, but "U1", "Location History #1", "Search History #1", "Browsing History #1", "Purchase History #1", and "Post History #1" are assumed to store specific information such as character strings and numbers.

[0082] The history information database 122 is not limited to the above and may store various types of information depending on the purpose. For example, the history information database 122 may store the user U's usage history of a predetermined service. The history information database 122 may also store the user U's store visit history or facility visit history. The history information database 122 may also store the user U's payment history (electronic payment) using the terminal device 10.

[0083] (control unit 130) 4, the explanation will be continued. The control unit 130 is a controller, and is realized by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like, executing various programs (corresponding to examples of information processing programs) stored in a storage device inside the information processing device 100 using a storage area such as a RAM as a working area. In the example shown in FIG. 4, the control unit 130 has an acquisition unit 131, a selection unit 132, a proposal unit 133, a provision unit 134, and a reception unit 135.

[0084] (Acquisition part 131) The acquisition unit 131 acquires posted comments linked to the distribution content. For example, when a user U posts a comment on the distribution content from the terminal device 10, the acquisition unit 131 acquires the posted comment linked to the distribution content via the communication unit 110. The acquisition unit 131 may store comments posted by each of multiple posters in relation to the distribution content in a database. Furthermore, the acquisition unit 131 may acquire multiple posted comments linked to the distribution content from a database in which multiple posted comments are linked to each distribution content or from an external storage.

[0085] Furthermore, the acquisition unit 131 acquires user information about the user U via the communication unit 110. For example, the acquisition unit 131 acquires identification information (such as a user UID) indicating the user U, location information of the user U, attribute information of the user U, and the like from the terminal device 10 of the user U. Furthermore, the acquisition unit 131 may acquire the identification information indicating the user U, the attribute information of the user U, and the like when registering the user U. Then, the acquisition unit 131 registers the user information in the user information database 121 of the storage unit 120.

[0086] Furthermore, the acquisition unit 131 acquires various types of history information (log data) indicating the behavior of the user U via the communication unit 110. For example, the acquisition unit 131 acquires various types of history information indicating the behavior of the user U from the terminal device 10 of the user U or from various servers based on the user UID or the like. Then, the acquisition unit 131 registers the various types of history information in the history information database 122 of the storage unit 120.

[0087] Furthermore, the acquisition unit 131 acquires a search query input by the user U. For example, when the user U inputs a search query into a search engine or the like to perform a keyword search, the acquisition unit 131 acquires the search query via the communication unit 110. That is, the acquisition unit 131 acquires, via the communication unit 110, the keywords input by the user U into the search box of a search engine, site, or app.

[0088] (Selection unit 132) The selection unit 132 estimates the user attributes of the user to whom a comment posting for another distribution content is proposed, based on information about the distribution content to which the comment was posted and information about the poster who posted the comment, and selects a user U with the estimated user attributes. The information about the distribution content is, for example, the title and content of the distribution content such as news (it may also be the source, theme, or category). The user attributes are, for example, a user segment, a user persona, etc.

[0089] The selection unit 132 may use machine learning to estimate the user attributes of users to whom comments on other distributed content are proposed, based on the title and content of the distributed content, such as news, and the user information of the comment poster. For example, the selection unit 132 uses the title and content of the distributed content, such as news, and the user information of the comment poster as input data, and generates an estimation model that outputs the user attributes of users to whom comments on other distributed content are proposed. Note that multiple user attributes may be output.

[0090] Alternatively, the selection unit 132 may use machine learning to generate an estimation model that uses as input data a set of the title and content of the distribution content, the user information of the comment poster, and the user attributes of the user to whom the comment posting of the other distribution content is proposed, and outputs a share score (or a share level), in order to estimate the user attributes of the user to whom the comment posting of the other distribution content is proposed, from the title and content of the distribution content such as news and the user information of the comment poster. The share score is a score that indicates the degree of relevance between information about the distribution content to which the comment was posted and the user information of the poster who posted the comment, and the user attributes of the user to whom the comment posting of the other distribution content is proposed.

[0091] The selection unit 132 may, for example, use image recognition and natural language processing to vectorize the title and content of the distribution content, the user information of the comment poster, and the user attributes of the user to whom the comment posting of other distribution content is proposed, and calculate the share score using the cosine similarity of each vector.

[0092] The selection unit 132 may use machine learning to generate an estimation model that uses a set of the title and content of the distribution content, the user information of the comment poster, and the share score as input data, and outputs the user attributes of users to whom comments on other distribution content are proposed or users with those user attributes. The selection unit 132 inputs a predetermined share score into the estimation model, and acquires, for example, the user attributes of users to whom comments on other distribution content are proposed, or users with those user attributes, who are not connected to the content of the distribution content based on the behavioral history of user U.

[0093] The selection unit 132, for example, selects a user with a user attribute having a predetermined share score as a user U to whom a comment posting for another distributed content is to be proposed. Alternatively, the selection unit 132 may present a plurality of users with a user attribute having a predetermined share score as candidates to the comment poster, and allow the comment poster to select a user U to whom a comment posting for another distributed content is to be proposed.

[0094] (Proposal Department 133) The suggestion unit 133 suggests to the user U selected by the selection unit 132 that he post a comment on another distributed content through content including the distributed content, the comment, and a suggestion for posting a comment on the other distributed content, based on the previously posted comment, the distributed content on which the comment was posted, and a new theme setting. For the other distributed content, a new theme setting may be made, for example, such as "What do you think? Tell us your article on XX," or the selected user U may set a new theme himself and select another distributed content.

[0095] The suggestion unit 133 may extract a request such as "What do you think? Tell me about your article on XX" from the posted comments, determine a user U with the user attribute of the proposed user from the extracted request, and make a suggestion to encourage the user U to post a comment in accordance with the request. At this time, the suggestion unit 133 may estimate a user attribute (which may be a user segment or a user persona) based on the extracted request. Furthermore, the suggestion unit 133 may also subtly prompt a user U with the user attribute of the proposed user to post, such as "What do you think? Tell me about your article on XX."

[0096] (Provider 134) When a certain number of shares have been shared, the providing unit 134 creates a list of the shared users, the distributed content, its theme, and comments, and generates share chain content including a share chain consisting of posted comments linked to the distributed content and posted comments linked to other distributed content, and flow points that provide an overview of the sharing trend, and provides this to user U.

[0097] 7 is a diagram showing an example of a share chain content provided by the providing unit 134 and displayed on the display unit 12 of the terminal device 10. In the example shown in FIG. 7, a share chain content 200 is displayed on the display unit 12 of the terminal device 10.

[0098] When a certain number of shares have been shared, the providing unit 134 inputs a prompt including, for example, the content of the shared distribution content and the content of the posted comments on it, and a sentence or the like that specifies the generation of a flow point that overlooks the sharing trend into the generation model, and obtains a flow point that overlooks the sharing trend. The generation model may be, for example, a GPT model. In the example shown in FIG. 7, a flow point 201 that overlooks the sharing trend is displayed in the sharing chain content 200, and for example, it displays, "This group has a chain centered on '...'. Due to '...', there is a '...' trend. '○○●' is connected to '☆★☆'."

[0099] In addition, the providing unit 134 may generate and provide suggested content to the user U selected by the selecting unit 132, suggesting that the user post a comment on other distributed content based on previously posted comments, the distributed content on which the comment was posted, and the new theme setting.

[0100] Furthermore, the providing unit 134 does not deliver suggestions or suggested content to users other than the user U selected by the selecting unit 132, but provides only the delivered content and the posted comments thereon.

[0101] (Reception Department 135) The reception unit 135 receives, via the communication unit 110, posted comments linked to the distribution content made in response to the proposal or distribution of the proposed content from the terminal device 10 of a user U who has been suggested to post a comment on other distribution content or who has received distribution of the proposed content.

[0102] [5. Processing Procedure] Next, a processing procedure by the information processing device 100 according to the embodiment will be described with reference to Fig. 8. Fig. 8 is a flowchart showing the processing procedure according to the embodiment. Note that the processing procedure shown below is repeatedly executed by the control unit 130 of the information processing device 100.

[0103] As shown in FIG. 8, the acquisition unit 131 of the information processing device 100 acquires posted comments linked to distribution content via the communication unit 110 (step S101).

[0104] Next, the acquisition unit 131 of the information processing device 100 acquires user information of the user U (comment poster) via the communication unit 110 (step S102).

[0105] Next, the selection unit 132 of the information processing device 100 estimates the user attributes of users who are proposed to post comments on other distribution content, and selects users with the estimated user attributes (step S103).

[0106] Next, the suggestion unit 133 of the information processing device 100 suggests to the proposed user U that he post a comment on another piece of distribution content (step S104).

[0107] Next, the acquisition unit 131 of the information processing device 100 acquires posted comments linked to other distribution content via the communication unit 110 (step S105).

[0108] Next, when the suggestion of comment posting is finished (step S106: Yes), the providing unit 134 of the information processing device 100 generates flow points that provide an overview of the sharing tendency of the distribution content and posted comments (step S107).

[0109] Next, the providing unit 134 of the information processing device 100 provides a chain content including the share chain and the flow point (step S108).

[0110] If the suggestion to post a comment is not to be terminated (step S106: No), the selection unit 132 of the information processing device 100 selects the user attributes (user segment or user persona) of the user to whom the comment posting for other distribution content is to be suggested (step S103).

[0111] [6. Modifications] The terminal device 10 and the information processing device 100 described above may be implemented in various different forms other than the above-described embodiment. Therefore, modifications of the embodiment will be described below.

[0112] In the above embodiment, some or all of the processing performed by the information processing device 100 may actually be performed by the terminal device 10. For example, the processing may be completed in a stand-alone manner (by the terminal device 10 alone). In this case, the terminal device 10 is assumed to have the functions of the information processing device 100 in the above embodiment. Furthermore, in the above embodiment, the terminal device 10 cooperates with the information processing device 100, and therefore, from the perspective of the user U, it appears that the processing of the information processing device 100 is also being performed by the terminal device 10. In other words, from another perspective, it can be said that the terminal device 10 is equipped with the information processing device 100.

[0113] For example, the terminal device 10 may execute the processing of the information processing device 100 in the above embodiment as processing on an installed app. That is, the processing of the information processing device 100 in the above embodiment may be processing on an app installed on the terminal device 10. In this case, the terminal device 10 may generate an estimation model through on-device learning. Alternatively, the terminal device 10 may cooperate with the information processing device 100, provide data to the information processing device 100, and acquire an estimation model generated by the information processing device 100 through machine learning. Note that the information processing device 100 may generate an estimation model for each user attribute (segment, persona). Furthermore, the terminal device 10 may cooperate with the information processing device 100 and generate an estimation model through federated learning.

[0114] Furthermore, in the above embodiment, news and the like are merely an example of distributed content. In reality, the distributed content may be a website where comments (or any other writings) can be posted, such as a bulletin board, as well as SNS, SMS (Short Message Service), a messaging app, and the like. Furthermore, the type (content) of the comment may be a product or service review, a questionnaire response, or the like.

[0115] [7. Effects] As described above, the information processing device (terminal device 10 and information processing device 100) according to the present application includes a selection unit 132 that selects a user U to whom a comment posting for other distributed content is to be suggested based on information about the distributed content to which the comment was posted and information about the poster who posted the comment, and a suggestion unit 133 that suggests to the suggested user U that they post a comment for other distributed content via content that includes the distributed content, the comment, and a suggestion for posting a comment for other distributed content.

[0116] The selection unit 132 estimates the user attributes of the user to whom a comment posting to other distribution content is proposed based on information about the distribution content to which the comment was posted and information about the poster who posted the comment, and selects a user U with the estimated user attributes.

[0117] The information processing device according to the present application further includes an acquisition unit 131 that acquires posted comments linked to distribution content.

[0118] The acquisition unit 131 acquires information about the poster of the posted comment linked to the distribution content.

[0119] The suggestion unit 133 extracts requests for posting specific content from the posted comments, and makes a suggestion to encourage users U with target user attributes to post comments that meet the requests.

[0120] The information processing device according to the present application further includes a receiving unit 135 that receives posted comments linked to other distribution content.

[0121] The information processing device according to the present application further includes a providing unit 134 that generates and provides share chain content including a share chain made up of a posted comment linked to a distribution content and a posted comment linked to another distribution content.

[0122] When the providing unit 134 inputs the sharing chain, it inputs the posted comments linked to the distribution content acquired by the acquiring unit 131 and the posted comments linked to other distribution content accepted by the accepting unit 135 into a generation model that generates flow points that provide an overview of the sharing trends, and generates flow points that provide an overview of the sharing trends, consisting of the posted comments linked to the distribution content acquired by the acquiring unit 131 and the posted comments linked to other distribution content accepted by the accepting unit 135.

[0123] The generative model in question is a GPT model.

[0124] The share chain content includes the points of the flow.

[0125] By using any one or a combination of the above-mentioned processes, the information processing device of the present application can suggest to appropriate users that they post comments on distributed content such as news, allow users to share the distributed content and posted comments among themselves, and visualize the chain of sharing between the distributed content and users as a series of changes.

[0126] [8. Hardware Configuration] The terminal device 10 and the information processing device 100 according to the above-described embodiments are realized by, for example, a computer 1000 configured as shown in Fig. 9. The following description will be given taking the information processing device 100 as an example. Fig. 9 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output I / F (Interface) 1060, an input I / F 1070, and a network I / F 1080 are connected via a bus 1090.

[0127] The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and the like, and executes various processes. The arithmetic device 1030 is realized by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like.

[0128] The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that temporarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device in which data used by the arithmetic device 1030 for various calculations and various databases are registered, and is realized by a ROM (Read Only Memory), an HDD (Hard Disk Drive), an SSD (Solid State Drive), a flash memory, or the like. The secondary storage device 1050 may be an internal storage device or an external storage device. The secondary storage device 1050 may also be a removable storage medium such as a USB (Universal Serial Bus) memory or an SD (Secure Digital) memory card. The secondary storage device 1050 may also be cloud storage (online storage), a NAS (Network Attached Storage), a file server, or the like.

[0129] The output I / F 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a display, a projector, a printer, etc., and is realized by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (High Definition Multimedia Interface), etc. The input I / F 1070 is an interface for receiving information from various input devices 1020, such as a mouse, a keyboard, a keypad, a button, a scanner, etc., and is realized by a USB, etc.

[0130] Furthermore, the output I / F 1060 and the input I / F 1070 may be wirelessly connected to the output device 1010 and the input device 1020, respectively. That is, the output device 1010 and the input device 1020 may be wireless devices.

[0131] The output device 1010 and the input device 1020 may be integrated into one device, such as a touch panel. In this case, the output I / F 1060 and the input I / F 1070 may also be integrated into one device as an input / output I / F.

[0132] The input device 1020 may be a device that reads information from, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0133] The network I / F 1080 receives data from other devices via the network N and sends it to the arithmetic device 1030, and also transmits data generated by the arithmetic device 1030 to other devices via the network N.

[0134] The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output I / F 1060 and the input I / F 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040 and executes the loaded program.

[0135] For example, when the computer 1000 functions as the information processing device 100, the arithmetic unit 1030 of the computer 1000 executes a program loaded onto the primary storage device 1040 to realize the functions of the control unit 130. The arithmetic unit 1030 of the computer 1000 may also load a program acquired from another device via the network I / F 1080 onto the primary storage device 1040 and execute the loaded program. The arithmetic unit 1030 of the computer 1000 may also cooperate with the other device via the network I / F 1080 to call and use the functions and data of a program from another program of the other device.

[0136] [9. Other] Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. Furthermore, the above-described components include those that can be easily imagined by a person skilled in the art, those that are substantially the same, and those that are within the scope of so-called equivalents. Furthermore, the above-described components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the components can be made without departing from the spirit of the above-described embodiments.

[0137] 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 all or part of the processes described as being performed manually can be performed automatically using a known method. In addition, the information including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

[0138] Furthermore, the components of each device shown in the figure are conceptual functional components and do 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.

[0139] For example, the information processing device 100 described above may be realized by multiple server computers, and depending on the function, the configuration can be flexibly changed, such as by calling an external platform using an API (Application Programming Interface) or network computing.

[0140] Furthermore, the above-described embodiments and modifications can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0141] Furthermore, the above-mentioned "section, module, unit" can be read as "means" or "circuit," etc. For example, an acquisition unit can be read as an acquisition means or an acquisition circuit. [Explanation of symbols]

[0142] 1. Information Processing Systems 10 Terminal Equipment 100 Information processing device 110 Communications Department 120 Storage section 121 User Information Database 122 Historical Information Database 130 control section 131 Acquisition Department 132 Selection section 133 Proposal Department 134 Provision Department 135 Reception

Claims

1. a selection unit that selects a user to whom a comment posting for another distribution content is to be proposed based on information about the distribution content to which the comment was posted and information about the poster who posted the comment; a suggestion unit that suggests to the user to post a comment on another distribution content via content including the distribution content, the comment, and a suggestion to post a comment on the other distribution content; An information processing device comprising:

2. The selection unit estimates user attributes of users to whom comments are to be posted on other content based on information about the content and information about the contributor, and selects users with the estimated user attributes.

2. The information processing apparatus according to claim 1, wherein:

3. an acquisition unit that acquires posted comments linked to distribution content; 3. The information processing apparatus according to claim 2, further comprising:

4. The acquisition unit acquires information about a poster of a comment linked to the distribution content.

4. The information processing apparatus according to claim 3,

5. The suggestion unit extracts requests for posting specific content from the posted comments and makes suggestions to encourage users with target user attributes to post comments in accordance with the requests.

4. The information processing apparatus according to claim 3,

6. a reception unit that receives posted comments linked to the other distribution content; 4. The information processing apparatus according to claim 3, further comprising:

7. a provider that generates and provides share chain content including a share chain consisting of a posted comment linked to the distribution content and a posted comment linked to the other distribution content; 7. The information processing apparatus according to claim 6, further comprising:

8. When the sharing chain is input, the providing unit inputs the posted comments linked to the distribution content acquired by the acquiring unit and the posted comments linked to the other distribution content accepted by the accepting unit to a generation model that generates flow points overlooking the sharing tendency, and generates flow points overlooking the sharing tendency, the flow points being composed of the posted comments linked to the distribution content acquired by the acquiring unit and the posted comments linked to the other distribution content accepted by the accepting unit.

8. The information processing apparatus according to claim 7,

9. The generative model is a GPT (Generative Pretrained Transformer) model.

9. The information processing apparatus according to claim 8,

10. The share chain content includes the points of the flow 10. The information processing device according to claim 8, wherein the information processing device is a computer.

11. An information processing method executed by an information processing device, a selection step of selecting a user to whom a comment posting to another distribution content is to be proposed based on information about the distribution content to which the comment was posted and information about the poster who posted the comment; a suggestion step of suggesting to the proposed user to post a comment on the other distributed content via content including the distributed content, the comment, and a suggestion to post a comment on the other distributed content; An information processing method comprising:

12. a selection step of selecting a user to whom a comment posting to another distribution content is to be suggested based on information about the distribution content to which the comment was posted and information about the poster who posted the comment; a suggestion step of suggesting to the proposed user to post a comment on the other distributed content via content including the distributed content, the comment, and a suggestion to post a comment on the other distributed content; An information processing program characterized by causing a computer to execute the above.

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