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

Abstract

To provide an information processing apparatus, an information processing method, and an information processing program, for allowing a comment to be easily browsed.SOLUTION: In an information processing system in which an information processing apparatus, a plurality of terminal devices, and a plurality of poster devices are connected by wire or wirelessly so as to communicate with each other over a network, the information processing apparatus 1 includes an extraction unit 43, a comment classification unit 44, and a provision unit 47. The extraction unit 43 extracts a plurality of comments posted by a user having a specific attribute, out of multiple comments posted to content. The comment classification unit 44 classifies each of the comments extracted by the extraction unit 43 into groups that satisfy a classification condition, out of multiple groups. The provision unit 47 provides provision information including classification information that indicates results classified by the comment classification unit 44.SELECTED DRAWING: Figure 4

Description

Technical Field

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

Background Art

[0002] Conventionally, when providing content such as news, a service is provided that provides content indicating opinions, feelings, etc. regarding content posted by a third party in accordance with the content (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the above prior art, although it is possible to provide a plurality of contents included in a specified theme and a plurality of comments posted on these plurality of comments, there is still room for further improvement in terms of facilitating the viewing of comments when the number of comments provided is large.

[0005] The present application has been made in view of the above, and an object thereof is to provide an information processing apparatus, an information processing method, and an information processing program capable of facilitating the viewing of comments.

Means for Solving the Problems

[0006] The information processing device according to this application comprises an extraction unit, a comment classification unit, and a provision unit. The extraction unit extracts multiple comments posted on content that are posted by users with specific attributes. The comment classification unit classifies each of the multiple comments extracted by the extraction unit into a group that satisfies classification criteria from among multiple groups. The provision unit provides provision information that includes classification information showing the results of the classification by the comment classification unit. [Effects of the Invention]

[0007] According to one embodiment, the effect is that comments can be easily viewed. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 shows an example of information processing according to the embodiment. [Figure 2] Figure 2 shows an example of the configuration of an information processing system according to the embodiment. [Figure 3] Figure 3 shows an example of the configuration of a terminal device according to this embodiment. [Figure 4] Figure 4 shows an example of the configuration of an information processing device according to the present invention. [Figure 5] Figure 5 shows an example of a user information table stored in the user information storage unit according to the embodiment. [Figure 6] Figure 6 shows an example of a content table stored in the content storage unit according to this embodiment. [Figure 7] Figure 7 shows an example of list content provided by the information processing unit according to the embodiment. [Figure 8] Figure 8 shows an example of content provided by the information processing device according to this embodiment. [Figure 9] Figure 9 shows an example of comment content provided by the information processing unit according to the embodiment. [Figure 10]Figure 10 shows another example of comment content provided by the information processing unit according to the embodiment. [Figure 11] Figure 11 is a flowchart showing an example of information processing by the processing unit of the information processing device according to the embodiment. [Figure 12] Figure 12 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing device according to the embodiment. [Modes for carrying out the invention]

[0009] The following describes in detail, with reference to the drawings, the embodiments for implementing the information processing apparatus, information processing method, and information processing program according to the present application (hereinafter referred to as "embodiments"). Note that these embodiments do not limit the information processing apparatus, information processing method, and information processing program according to the present application. Furthermore, each embodiment can be appropriately combined as long as the processing content is not inconsistent. Also, the same parts are denoted by the same reference numerals in each of the following embodiments, and redundant descriptions are omitted.

[0010] [1. An example of information processing] First, an example of information processing according to the embodiment will be described using Figure 1. Figure 1 is a diagram showing an example of information processing according to the embodiment.

[0011] The information processing device 1 shown in Figure 1 provides online services such as news sites, shopping sites, auction sites, flea market sites, restaurant review sites, review sites, or SNS (Social Networking Service) sites.

[0012] As shown in Figure 1, the information processing device 1 controls users U1 to U n-1 Content requested by user U1~U n-1 Provided (Steps S11~S1 n-1 n is, for example, an integer greater than or equal to 3.

[0013] Steps S11 to S1 n-1 The content provided in n-1 is, for example, content related to products to be traded on shopping sites or auction sites, news content, or content related to products or services that are the subject of reviews on review sites, etc., and may be referred to as target content hereinafter.

[0014] For example, users U1 to U n-1 operate the corresponding terminal device among terminal devices 21 to 2 n-1 to cause the information processing device 1 to send a content request from the corresponding terminal device among terminal devices 21 to 2 n-1 The information processing device 1 sends the target content corresponding to the content request sent from terminal devices 21 to 2 n-1 to terminal devices 21 to 2 n-1 and causes terminal devices 21 to 2 n-1 to display the target content corresponding to the content request, thereby providing the target content corresponding to the request from users U1 to U n-1 to users U1 to U n-1 .

[0015] Then, the information processing device 1 accepts the posting of comments on the target content from users U1 to U n-1 (Steps S21 to S2 n-1 ). The information processing device 1 stores the comment information received from users U1 to U n-1 (Step S3). For example, users U1 to U n-1 operate the corresponding terminal device among terminal devices 21 to 2 n-1 to cause the corresponding terminal device among terminal devices 21 to 2 n-1 to send the comment information on the target content to the information processing device 1.

[0016] The information processing device 1 receives the comment information sent from terminal devices 21 to 2 n-1 and stores the received comment information, thereby n-1The system stores information about comments received. Below, the users U1~U who posted the comments are listed. n-1 Each of these may be referred to as a posting user, and comments posted to the target content may be referred to as posted comments.

[0017] The information processing device 1 classifies multiple posting users into groups according to the attributes of the posting users (step S4). In the process of step S4, the information processing device 1 classifies multiple posting users into groups for each combination of multiple attribute items. Attribute items include, for example, gender, age, occupation, and location.

[0018] For example, the information processing device 1 can classify multiple posting users into groups based on combinations of multiple attribute items, such as groups based on combinations of gender and age. Examples of groups based on gender and age combinations include groups of men in their 20s, groups of women in their 20s, groups of men in their 30s, groups of women in their 30s, and so on.

[0019] Furthermore, the information processing device 1 can also classify multiple posting users into groups based on attribute items. For example, the information processing device 1 can classify multiple posting users into groups based on gender or age group. Groups based on gender may include groups of men, groups of women, and groups of unknown gender. Groups based on age group may include groups of teenagers, groups of people in their twenties, groups of people in their thirties, etc. In the following, groups based on combinations of multiple attribute items or groups based on individual attribute items may be referred to as attribute groups.

[0020] Subsequently, the information processing device 1 controls user U n The information processing device 1 receives a content request from the terminal device 2 (step S5). Then, the information processing device 1 provides the content in accordance with the content request (step S6). In the process of step S6, the information processing device 1 provides the content to the terminal device 2 n Send to terminal device 2 n By displaying it on the user U nWe provide content to them.

[0021] The provided content includes target content corresponding to the content request, attribute selection content containing tags for each of the multiple attribute groups classified in step S4, and comment content containing multiple posted comments for the target content corresponding to the content request. Such provided content is an example of the information to be provided.

[0022] In the example shown in Figure 1, the provided content includes News K content containing the string "How to evaluate teleworking employees..." as the target content in response to the content request, tags for multiple attribute groups as attribute selection content, and posted comment C as comment content. A-3 ,C B-2 This includes information such as [information omitted].

[0023] The attribute selection content included in Figure 1 contains tags for multiple attribute groups, including tags for the attribute group of men in their 30s, women in their 30s, men in their 40s, women in their 20s, men in their 20s, and women in their 40s. In the following, attribute group tags may be referred to as attribute tags.

[0024] The information processing device 1 places attribute tags in attribute groups with a large number of classified posting users higher in the sorting order within the attribute selection content. In the attribute selection content shown in Figure 1, the attribute tag for men in their 30s is in the highest position, and the attribute tag for women in their 30s is in the second highest position.

[0025] User U n Terminal device 2 n By manipulating this, one attribute tag can be selected from among multiple attribute tags in the attribute selection content shown in Figure 1. For example, User U nIn the provided content, you can select attribute tags for men in their 30s by selecting attribute tags that contain the string "men in their 30s," and you can select attribute tags for women in their 30s by selecting attribute tags that contain the string "women in their 30s."

[0026] User U n If the terminal device 2 selects one attribute tag from among multiple attribute tags, n From user U n Selection information indicating the information of the selected attribute tag is transmitted to the information processing device 1 (step S7).

[0027] Information processing device 1 is connected to terminal device 2 n Multiple posts and comments made by multiple posting users classified into attribute groups corresponding to attribute tags indicated by the selected information are classified into multiple groups (step S8). In the following, attribute groups corresponding to attribute tags indicated by the selected information may be referred to as selected attribute groups, posting users classified into selected attribute groups may be referred to as target posting users, and posts made by target posting users may be referred to as target posts and comments. In addition, in the following, groups of comments classified in step S8 may be referred to as comment groups.

[0028] In step S8, the information processing device 1 classifies the multiple target posted comments into a group of comment groups that satisfy the classification criteria. The classification criteria are, for example, one or more of the following: conditions relating to the content of the target posted comments, conditions relating to the attributes of the target posting user, conditions relating to the behavioral history of the target posting user, and conditions relating to the posting date and time and posting location of the target posted comments.

[0029] For example, the information processing device 1 can classify each of the multiple target posted comments into a comment group according to the content of the target posted comment. The conditions regarding the content of the target posted comment are, for example, the conditions regarding the type of evaluation of the target content. The types of evaluation are, for example, positive evaluation, negative evaluation, and neutral evaluation.

[0030] Furthermore, the information processing device 1 can classify each of the multiple target posted comments into a comment group according to the attributes of the target posting user. The conditions regarding the attributes of the target posting user are, for example, attribute items that are some or all different from the attribute items used for classification in step S4, but are not limited to such examples.

[0031] Furthermore, the information processing device 1 can classify each of the multiple target posted comments into a comment group according to the behavioral history of the target posting user. The conditions related to the behavioral history of the target posting user include, for example, conditions regarding the target posting user's content viewing tendencies, conditions regarding the target posting user's purchase tendencies for transaction items, and conditions regarding the payment amount by the target posting user.

[0032] Furthermore, the information processing device 1 can classify each of the multiple target posted comments into a comment group according to the posting date and time and posting location of the target posted comment. The posting date and time is the date and time when the target posting user posted the target posted comment, and the posting location is the location of the target posting user when the target posted comment was posted.

[0033] Next, the information processing device 1 identifies the keywords for each of the multiple comment groups into which the multiple target posted comments were classified in step S8 (step S9). In the process of step S9, the information processing device 1 can, for example, calculate the TF-IDF (Term Frequency-Inverse Document Frequency) value of the words or phrases contained in the comments for each comment group, and based on these TF-IDF values, extract characteristic words or phrases for each comment group as keywords for each comment group.

[0034] Next, the information processing device 1 sends comment content to the terminal device 2, which includes as classification information a pie chart showing the number of comments classified into each comment group, and a graph showing the keywords for each comment group identified in step S9 as the content for each comment group.n By sending it, user U n Provide comment content (Step S10).

[0035] The comment content shown in Figure 1 includes classification information in the form of a graph that indirectly shows the ratio of the number of comments in each of three comment groups, into which multiple comments posted by a male user in his 30s have been classified.

[0036] In the comment content shown in Figure 1, the keywords for the first comment group are "good" and "new," the keywords for the second comment group are "bad" and "useless," and the keywords for the third comment group are "meaningless" and "neither."

[0037] Furthermore, the comment content shown in Figure 1 includes multiple comments C posted by a male user in his 30s. A-9 ,C A-6 ,C A-3 This includes information such as that of user U. n User U n Multiple post comments C posted by target posting users included in the attribute group selected by A-9 ,C A-6 ,C A-3 Because it can be confirmed, user U n Multiple posted comments categorized into the selected attribute group can be easily identified.

[0038] The information processing device 1 may be configured to execute the process in step S8 before the process in step S5, or it may be configured to execute the processes in steps S8 and S9 before the process in step S5.

[0039] Furthermore, the provided content and comment content will be available on terminal devices 21-2 nIt may also be displayed by the processing of the main body, and via an interface such as an API (Application Programming Interface) to terminal devices 21-2 n Based on the information input from terminal devices 21-2, the information processing device 1 processes the information input from terminal devices 21-2. n It may also be something that is displayed on. Also, in Figure 1, terminal devices 21-2 n The case where the terminal devices 21-2 and the information processing device 1 are separate devices was shown, but terminal devices 21-2 n The information processing device 1 may be integrated into a single unit.

[0040] In this way, the information processing device 1 extracts multiple comments posted by users with specific attributes from among multiple comments posted on the content, and classifies each of the extracted comments into one of several groups that meets the classification criteria. The information processing device 1 then provides information including classification information that shows the classification results. This makes it easy for the information processing device 1 to view the posted comments.

[0041] The following describes the information processing device 1 and multiple terminal devices 21-2 that perform such processing. n This document provides a detailed explanation of the configuration of the information processing system, including the following:

[0042] [2. Configuration of the Information Processing System] Figure 2 is a diagram showing an example of the configuration of an information processing system according to the embodiment. As shown in Figure 2, the information processing system 100 according to the embodiment includes an information processing device 1 and a plurality of terminal devices 21-2 n and multiple submitter devices 31-3 m This includes m, where m is an integer greater than or equal to 2.

[0043] Information processing device 1, terminal devices 21-2 n , and submitter equipment 31-3 m These devices are connected to each other via a network N, either by wire or wireless connection, enabling communication between them. Note that the information processing system 100 shown in Figure 2 may include multiple information processing devices 1.

[0044] Information processing device 1 provides online services such as news sites, shopping sites, auction sites, flea market sites, restaurant review sites, review sites, or social networking sites.

[0045] Multiple terminal devices 21-2 n Each of these may be, for example, a desktop PC (Personal Computer), a notebook PC, a tablet device, a smartphone, a mobile phone, or a PDA (Personal Digital Assistant). Multiple terminal devices 21-2 n Each of these is a multiple user U1~U n It is operated by the corresponding user.

[0046] Note that multiple terminal devices 21-2 n Each of these is not limited to the examples above, and may be, for example, a smartwatch or a wearable device. Also, in the following, multiple terminal devices 21-2 n When referring to each of them without individually distinguishing them, they may be written as Terminal Device 2. Also, multiple users U1~U n When referring to each of these without individually distinguishing them, they may be written as User U.

[0047] Multiple submitter devices 31-3 m Each of these is an information processing device that receives target content provided by the online service provided by information processing device 1. For example, multiple submitter devices 31-3 m Each of these transmits to the information processing device 1 the target content, such as news content, content related to products traded on shopping sites or auction sites, or content related to products or services that are the subject of reviews on review sites. In the following, multiple input devices 31-3 m When referring to each of these without individually distinguishing them, they may be described as "Submitter Device 3".

[0048] [3. Terminal device 2] Figure 3 shows an example of the configuration of the terminal device 2 according to the embodiment. As shown in Figure 3, the terminal device 2 according to the embodiment includes a communication unit 10, a display unit 11, an operation unit 12, a sensor group 13, a storage unit 14, and a processing unit 15.

[0049] [3.1. Communications Section 10] The communication unit 10 is implemented, for example, by a NIC (Network Interface Card). The communication unit 10 is connected to the network N by wire or wireless connection and transmits and receives information to and from the information processing device 1 via the network N.

[0050] [3.2. Display section 11] The display unit 11 is, for example, an LCD (Liquid Crystal Display) or an organic EL (Electro Luminescence) display.

[0051] [3.3. Operation section 12] The operation unit 12 includes, for example, a keyboard with keys for entering letters, numbers, and spaces, an enter key and arrow keys, a mouse, and a power button. If the display unit 11 is a touch panel compatible display, the operation unit 12 includes a touch panel.

[0052] [3.4. Sensor Group 13] The sensor group 13 includes, for example, a positioning sensor, an accelerometer, a gyroscope, and an image sensor. The positioning sensor is a sensor that detects the position of the terminal device 2 as the position of user U. The accelerometer is a sensor that detects the acceleration of the terminal device 2. The gyroscope is a sensor that detects the attitude of the terminal device 2, such as its tilt and rotation. The image sensor is a sensor that captures images of the area around the terminal device 2.

[0053] [3.5. Storage section 14] The memory unit 14 is implemented by, for example, semiconductor memory elements such as RAM (Random Access Memory) and flash memory, or by storage devices such as hard disks and optical discs.

[0054] The storage unit 14 stores, for example, information transmitted from the information processing device 1 and acquired by the processing unit 15 via the network N and the communication unit 10, as well as detection information, which is information detected by the sensor group 13.

[0055] [3.6. Processing Unit 15] The processing unit 15 is a controller, and is implemented, for example, by a CPU (Central Processing Unit) or MPU (Micro Processing Unit) executing various programs stored in the memory device inside the terminal device 2 using RAM as the working area. The processing unit 15 may be partially or entirely implemented by an integrated circuit, for example, an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The processing unit 15 includes an information acquisition unit 16, a display processing unit 17, and an information output unit 18.

[0056] [3.6.1. Information acquisition unit 16] The information acquisition unit 16 acquires various content transmitted from the information processing device 1 and received by the communication unit 10 via the network N. The content transmitted from the information processing device 1 is, for example, the provided content and comment content mentioned above.

[0057] [3.6.2. Display Processing Unit 17] The display processing unit 17 displays the information acquired by the information acquisition unit 16 on the display unit 11. For example, the display processing unit 17 displays content acquired by the information acquisition unit 16 on the display unit 11.

[0058] [3.6.3. Information Output Unit 18] The information output unit 18 transmits, for example, operation information corresponding to operations performed by user U on the operation unit 12 to the information processing device 1 via the communication unit 10. The information output unit 18 also transmits detection information, which is information detected by the sensor group 13, to the information processing device 1 via the communication unit 10.

[0059] [4. Configuration of Information Processing Device 1] Figure 4 shows an example of the configuration of an information processing device 1 according to an embodiment. As shown in Figure 4, the information processing device 1 has a communication unit 20, a storage unit 21, and a processing unit 22.

[0060] [4.1. Communications Section 20] The communication unit 20 is implemented, for example, by a NIC (Network Interface Card). The communication unit 20 is connected to the network N by wire or wireless connection and transmits and receives information with various other devices. For example, the communication unit 20 transmits and receives information with terminal device 2 and submitter device 3 via the network N.

[0061] [4.2. Storage section 21] The storage unit 21 is implemented by, for example, semiconductor memory elements such as RAM and flash memory, or storage devices such as hard disks and optical discs. The storage unit 21 has a user information storage unit 30 and a content storage unit 31.

[0062] [4.2.1. User Information Storage Unit 30] The user information storage unit 30 stores various information about user U. Figure 5 is a diagram showing an example of a user information table stored in the user information storage unit 30 according to this embodiment. In the example shown in Figure 5, the user information table stored in the user information storage unit 30 includes information on items such as "user ID," "attribute information," and "history information."

[0063] The "User ID" is an identifier that identifies User U. The "Attribute Information" is attribute information about User U's attributes associated with the "User ID". User U's attributes include, for example, demographic attributes and psychographic attributes. Demographic attributes are demographic attributes such as age, gender, occupation, place of residence, annual income, and family structure. Psychographic attributes are psychological attributes such as lifestyle, values, and interests.

[0064] "History information" refers to history information that includes information such as User U's service usage history (an example of behavioral history), and includes, for example, User U's payment history information, User U's search history information, and User U's browsing history information.

[0065] User U's payment history information includes purchase history information for goods purchased by User U online, in physical stores, or at physical facilities using payment services, and service usage history information for services used by User U for a fee online, in physical stores, or at physical facilities using payment services.

[0066] Purchase history information includes information about the products purchased by user U, purchase costs, purchase date and time, and store of purchase. Service usage history information includes information about the services used by user U, usage costs, usage date and time, and store of use.

[0067] User U's search history information includes, for example, information on web content searches on search engines and search history on various websites. User U's browsing history information includes information on product information that User U has viewed on various websites.

[0068] In the example shown in Figure 5, user U with user ID "U1" has attribute information "Attribute Information AT1" and history information "History Information AC1", user U with user ID "U2" has attribute information "Attribute Information AT2" and history information "History Information AC2", and user U with user ID "U3" has attribute information "Attribute Information AT3" and history information "History Information AC3".

[0069] In the example shown in Figure 5, attribute information and history information are represented by abstract strings such as "Attribute Information AT1" to "Attribute Information AT3" and "History Information AC1" to "History Information AC3," but attribute information and history information can be, for example, text data or data in file format. Furthermore, the user information storage unit 30 is not limited to the above and may store various types of information depending on the purpose.

[0070] [4.2.2. Content Storage Unit 31] The content storage unit 31 stores various information about the target content submitted from the submitter device 3, as well as information such as submitted comments and ratings transmitted from the terminal device 2. Figure 6 shows an example of a content table stored in the content storage unit 31 according to this embodiment. In the example shown in Figure 6, the content table stored in the content storage unit 31 includes information on items such as "Content ID," "Content," "Rating Information," and "Comment Information."

[0071] "Content ID" is an identifier that identifies the target content. "Content" is information that indicates the target content, such as information that indicates news content, information that indicates content related to products traded on shopping sites or auction sites, or information that indicates content related to products or services that are the subject of reviews on review sites.

[0072] "Rating information" is information that shows user U's evaluation of the target content or posted comments. Evaluations of the target content can be, for example, positive, neutral, or negative. Positive evaluations are made, for example, by user U selecting a positive rating button (e.g., selecting the "Good" button). Neutral evaluations are made, for example, by user U selecting a neutral rating button (e.g., selecting the "Average" button). Negative evaluations are made, for example, by user U selecting a negative rating button (e.g., selecting the "Bad" button).

[0073] Furthermore, evaluations of the target content do not necessarily have to include neutral evaluations, and evaluations such as "learnable," "easy to understand," or "offer a new perspective" may be used in addition to or instead of positive, neutral, or negative evaluations.

[0074] "Comment information" refers to information about posted comments, and for each posted comment, it includes an identifier that identifies the posted comment, an identifier that identifies the posting user, information indicating the date and time the comment was posted, information indicating the posting user's location when the comment was posted (posting location), information about the comment, and information indicating the rating of the comment. In addition, if there are comments on the posted comment, "comment information" also includes information about those comments.

[0075] In the example shown in Figure 6, the target content with content ID "CO1" has content information "Content C1", evaluation information "Evaluation Information E1", and comment information "Comment Information D1". Similarly, the target content with content ID "CO2" has content information "Content C2", evaluation information "Evaluation Information E2", and comment information "Comment Information D2". Furthermore, the target content with content ID "CO3" has content information "Content C3", evaluation information "Evaluation Information E3", and comment information "Comment Information D3".

[0076] In the example shown in Figure 6, the target content, evaluation information, and comment information are represented by abstract strings such as "Content C1" to "Content C3," "Evaluation Information E1" to "Evaluation Information E3," and "Comment Information D1" to "Comment Information D3." However, this information can be, for example, text data or data in file format. Furthermore, the content storage unit 31 is not limited to the above and may store various types of information depending on the purpose.

[0077] [4.3. Processing Unit 22] The processing unit 22 is a controller and is implemented, for example, by a processor such as a CPU or MPU, which executes various programs (an example of an information processing program) stored in a memory device (e.g., memory unit 21) inside the information processing device 1, using RAM as a working area. Alternatively, the processing unit 22 may be partially or entirely implemented by an integrated circuit such as an ASIC or FPGA.

[0078] As shown in Figure 4, the processing unit 22 includes an acquisition unit 40, a reception unit 41, an attribute classification unit 42, an extraction unit 43, a comment classification unit 44, a specification unit 45, a sorting order determination unit 46, and a provision unit 47, and realizes or executes the information processing functions and operations described below. Note that the internal configuration of the processing unit 22 is not limited to the configuration shown in Figure 4, and other configurations are also acceptable as long as they perform the information processing described later.

[0079] [4.3.1. Acquisition part 40] The acquisition unit 40 acquires various types of information. The acquisition unit 40 acquires various types of information from the storage unit 21. The acquisition unit 40 acquires various types of information from the user information storage unit 30 and the content storage unit 31, etc.

[0080] For example, the acquisition unit 40 acquires information from the storage unit 21 in response to requests and information received by the reception unit 41. For example, if the reception unit 41 receives a content list request, the acquisition unit 40 acquires multiple target content items of the type specified by the content list request from the content storage unit 31.

[0081] Furthermore, when a content request is received by the reception unit 41, for example, the acquisition unit 40 acquires information such as the target content identified by the content request and multiple posted comments made for the target content identified by the content request from the content storage unit 31.

[0082] Comments posted to the target content include, but are not limited to, comments posted indirectly to the target content, as well as comments posted directly to the target content. Indirect comments to the target content include, for example, comments posted in response to comments posted to the target content.

[0083] Furthermore, when the reception unit 41 receives selection information, the acquisition unit 40 acquires information such as multiple posted comments of the group identified by the selection information from the content storage unit 31. Also, when the reception unit 41 receives content requests or selection information, the acquisition unit 40 acquires information about user U identified by the content requests or selection information from the user information storage unit 30.

[0084] Furthermore, the acquisition unit 40 receives various information from an external information processing device via the communication unit 20. For example, the acquisition unit 40 acquires user information from an external device and stores the acquired user information in the user information storage unit 30. For example, the acquisition unit 40 acquires user information from an external device at predetermined intervals and updates the user information table stored in the user information storage unit 30.

[0085] [4.3.2. Reception Department 41] The reception unit 41 receives various requests from terminal devices 2 and submitter devices 3. For example, it receives submission requests transmitted from submitter devices 3 and received by the communication unit 20. Submission requests include the content to be submitted, and when the reception unit 41 receives a submission request, it adds the content included in the submission request to the content table stored in the content storage unit 31 and updates the content table.

[0086] The reception unit 41 receives a content list request transmitted from the terminal device 2 and received by the communication unit 20. The content list request includes, for example, information to identify user U (e.g., user ID), information to identify the type of target content, and detection information. The detection information is information detected by the sensor group 13 and includes, for example, information indicating the location of user U.

[0087] The reception unit 41 receives content requests transmitted from the terminal device 2 and received by the communication unit 20. The content request includes information to identify user U, information to identify the target content, and detection information.

[0088] Furthermore, the reception unit 41 receives selection information transmitted from the terminal device 2 and received by the communication unit 20. The selection information includes information for identifying user U, information about the group selected by user U from among multiple groups in which information is included in the provided content provided to user U, and detection information.

[0089] Furthermore, the reception unit 41 receives posted comment information transmitted from the terminal device 2 and received by the communication unit 20. The posted comment information includes information for identifying the posting user, information about the posted comment entered by user U, who is the posting user, into the terminal device 2, information for identifying the target content to which the posted comment applies, and detection information. When the reception unit 41 receives the posted comment information, it adds the received posted comment information to the content table stored in the content storage unit 31.

[0090] [4.3.3. Attribute classification section 42] The attribute classification unit 42 classifies, for each target content, multiple posting users who have posted comments on the target content into attribute groups, which are groups corresponding to the attributes of the posting users.

[0091] For example, the attribute classification unit 42 classifies multiple posting users into attribute groups for each combination of multiple attribute items. The attribute items are, for example, demographic attributes such as age, gender, occupation, place of residence, annual income, and family structure, but may also include psychographic attributes such as age, gender, occupation, place of residence, annual income, and family structure in addition to or instead of demographic attributes.

[0092] For example, the attribute classification unit 42 can classify multiple posting users into attribute groups based on combinations of multiple attribute items, such as attribute groups based on combinations of gender and age. Examples of attribute groups based on combinations of gender and age include groups of men in their 20s, attribute groups of women in their 20s, attribute groups of men in their 30s, attribute groups of women in their 30s, and so on.

[0093] Furthermore, the attribute classification unit 42 can also classify multiple posting users into attribute groups for each attribute item. For example, the attribute classification unit 42 can classify multiple posting users into attribute groups by gender or attribute groups by age group. Attribute groups by gender may include groups for men, groups for women, and groups for unknowns. Attribute groups by age group may include, for example, groups for teenagers, groups for people in their 20s, and groups for people in their 30s.

[0094] [4.3.4. Extraction part 43] The extraction unit 43 extracts multiple comments posted on the target content that were posted by users with specific attributes. These specific attributes are those indicated by attribute groups.

[0095] For example, the extraction unit 43 extracts multiple comments posted on the target content at a predetermined timing, specifically those posted by users with certain attributes.

[0096] The predetermined timings include, for example, the timing when selection information including attribute tag information is received by the reception unit 41, the timing that occurs at predetermined intervals, or the timing when posted comment information is received by the reception unit 41.

[0097] The extraction unit 43 extracts multiple posted comments from multiple posting users classified into attribute groups indicated by attribute tags indicated by the selection information received by the reception unit 41. The extraction unit 43 can also extract multiple posted comments for target content for each attribute group at predetermined intervals.

[0098] Furthermore, the extraction unit 43 can also extract multiple posted comments from users classified into attribute groups corresponding to the attributes of the posting user in the posted comment information, at the time the posting comment information is received by the reception unit 41. In the following, multiple posted comments from users with specific attributes may be referred to as multiple comments from an attribute group.

[0099] Furthermore, the extraction unit 43 can also extract multiple posted comments posted by posting users who possess specific attributes, by defining attributes that match or are similar to the attributes of the recipient user, who is the user of the terminal device 2 that sent the content request, as specific attributes.

[0100] For example, the extraction unit 43 determines that attributes whose similarity to the attributes of the recipient user is above a threshold are specific attributes. The similarity of attributes increases as the number of matching items, or the degree of matching, such as the user's gender, age, occupation, and location (or place of residence), increases.

[0101] Furthermore, the extraction unit 43 can extract multiple comments posted by posting users with specific attributes for each of the multiple periods. The multiple periods may be different from each other, but may also overlap in some parts.

[0102] For example, multiple periods could be the period up to 24 hours ago, the period more than one day ago, the entire period, etc., but they could also be the period up to 24 hours ago, the period from 24 hours ago to one week ago, the period more than one week ago, etc., or periods in predetermined units (for example, one day or one week).

[0103] [4.3.5. Comment Classification Section 44] The comment classification unit 44 performs a classification process in which each of the multiple posted comments of the attribute group extracted by the extraction unit 43 is classified into one of the multiple comment groups that satisfies the classification criteria. The classification process by the comment classification unit 44 is performed on an attribute group basis.

[0104] The classification criteria include, for example, one or more of the following: criteria related to the content of the posted comment, criteria related to the attributes of the posting user, criteria related to the posting user's activity history, and criteria related to the posting date and time and location of the posted comment.

[0105] For example, the comment classification unit 44 can classify each of multiple posted comments into a group according to the content of the comment. The conditions regarding the content of the posted comment are, for example, the conditions regarding the type of evaluation of the target content. The types of evaluation are, for example, positive evaluation, negative evaluation, and neutral evaluation.

[0106] In this case, the comment classification unit 44 classifies the multiple posted comments into one of three groups based on the content of the posted comments: a group of posted comments that show a positive evaluation of the target content, a group of posted comments that show a negative evaluation of the target content, or a group of posted comments that show a neutral evaluation of the target content.

[0107] Furthermore, the conditions regarding the content of submitted comments may also include, for example, conditions regarding the political leanings of the comments if the target content is news content related to politics. These political leanings may include, for example, conservative, centrist, and progressive.

[0108] In this case, the comment classification unit 44 classifies the multiple posted comments into one of three groups based on the content of the posted comments: a group of posted comments that show conservative content regarding the target content, a group of posted comments that show neutral content regarding the target content, or a group of posted comments that show innovative content regarding the target content.

[0109] The comment classification unit 44 has a comment classification model, and inputs information about posted comments (e.g., text information) into the comment classification model. It then classifies the posted comments into the group with the highest score among the group scores output by the comment classification model.

[0110] The comment classification unit 44 can, for example, use a dataset containing information on posted comments and information indicating group labels as training data to generate a comment classification model by machine learning.

[0111] For example, comment classification models include models that take information from posted comments as input and output scores for positive, negative, and neutral ratings, and models that take information from posted comments as input and output scores for conservative, moderate, and innovative ratings.

[0112] Furthermore, the conditions regarding the content of the posted comments may include, for example, the degree to which they are constructive. In this case, the comment classification model may be, for example, a model that takes information about the posted comments as input and outputs a construction score.

[0113] The construction score is a score that indicates the degree to which the content is constructive, with the construction score being higher for representative comments that are constructive. The comment classification unit 44 inputs the information of the posted comments into the comment classification model and classifies the posted comments into groups that include the construction score output by the comment classification model.

[0114] Furthermore, the comment classification unit 44 may be configured to classify multiple posted comments by, for example, dividing the information of a posted comment into multiple morphemes by morphological analysis, and then analyzing the strings of specific parts of speech, such as nouns and verbs, contained in the multiple decomposed morphemes.

[0115] In this case, the comment classification unit 44 classifies, for example, whether the posted comment to be classified is a posted comment indicating a positive evaluation, a posted comment indicating a negative evaluation, or a posted comment indicating a neutral evaluation.

[0116] Furthermore, the comment classification unit 44 can classify each of the multiple posted comments into groups according to the attributes of the posting user. The conditions regarding the posting user's attributes may be different from the attribute items used for classification in the attribute classification unit 42, but may be attribute items that partially overlap. For example, if the attribute items used for classification in the attribute classification unit 42 are gender and age, the conditions regarding the posting user's attributes may be multiple attribute items including gender, age and occupation, multiple attribute items including gender, age and annual income, or multiple attribute items including gender, age and place of residence.

[0117] The conditions related to the posting user's behavior history include, for example, conditions regarding the posting user's content viewing tendencies, conditions regarding the posting user's purchase tendencies for the items being traded, and conditions regarding the amount of money paid by the posting user.

[0118] For example, suppose the conditions related to the posting user's behavior history are the conditions related to the posting user's tendency to view news content. In this case, the comment classification unit 44 classifies multiple posted comments into groups according to their tendency to view news content. For example, the comment classification unit 44 classifies multiple posted comments into one of the following groups: a group of posted comments posted by users whose frequency of viewing news content is less than the first threshold, a group of posted comments posted by users whose frequency of viewing news content is between the first threshold and the second threshold, or a group of posted comments posted by users whose frequency of viewing news content is at or above the second threshold.

[0119] Furthermore, the comment classification unit 44 classifies multiple posted comments into one of several groups, such as a group of comments posted by users who most frequently view entertainment news content, a group of comments posted by users who most frequently view sports news content, or a group of comments posted by users who most frequently view economic news content.

[0120] Furthermore, the conditions related to the posting user's behavioral history are used as conditions for the posting user's purchase tendency of the transaction target. In this case, the comment classification unit 44 classifies multiple posted comments into groups according to the purchase tendency of the transaction target. For example, the comment classification unit 44 classifies them into either a group of posted comments posted by the posting user with the highest purchase frequency at online shops, or a group of posted comments posted by the posting user with the highest purchase frequency at physical stores.

[0121] Furthermore, the conditions related to the posting user's activity history are set to the amount of payment made by the posting user. In this case, the comment classification unit 44 classifies multiple posted comments into groups according to the amount of payment. For example, the comment classification unit 44 classifies multiple posted comments into one of the following groups: a group of posted comments made by posting users whose payment amount per unit period is less than the first threshold, a group of posted comments made by posting users whose payment amount per unit period is between the first threshold and the second threshold, or a group of posted comments made by posting users whose payment amount per unit period is equal to or greater than the second threshold.

[0122] Furthermore, the comment classification unit 44 can classify each of the multiple posted comments into groups according to the posting date and time and posting location of the comment. The posting date and time is the date and time when the posting user posted the comment, and the posting location is the location of the posting user when the comment was posted, which is the location indicated by the posting user detection information included in the submission request.

[0123] In this case, the comment classification unit 44 classifies multiple posted comments into groups according to their posting date and time. For example, the comment classification unit 44 classifies multiple posted comments into one of three groups: a group of comments posted within the last 24 hours, a group of comments posted up to one week ago, or a group of comments posted more than one week ago.

[0124] Furthermore, the comment classification unit 44 can also classify multiple posted comments into groups based on their posting location or combinations of posting date and time and posting location. For example, the comment classification unit 44 can classify multiple posted comments into groups of comments posted in the Kanto region, groups of comments posted in the Kansai region, and groups of comments posted in regions other than the Kanto and Kansai regions. The comment classification unit 44 can also classify comments into groups based on combinations of posting date and time and posting location.

[0125] The classification criteria may vary depending on the type of content and the attributes of the recipient user. If the content is news, the types of content may include sports, politics, economics, entertainment, international affairs, etc. The recipient user is the user who receives the content, including the content and posted comments, and is user U of terminal device 2 who sent the content request.

[0126] For example, the comment classification unit 44 can classify multiple posted comments using different classification conditions for each type of target content, or classify multiple posted comments using different classification conditions for each attribute of the recipient user. Furthermore, the comment classification unit 44 can classify multiple posted comments using classification conditions based on the recipient user's location, or classify multiple posted comments using classification conditions based on both the recipient user's attributes and location.

[0127] Furthermore, the classification conditions used by the comment classification unit 44 can be set by the provider of the target content from among the multiple types of conditions described above. The comment classification unit 44 can also sequentially change the classification conditions used from among the multiple types of classification conditions. In this case, the comment classification unit 44 can also decide to use the classification condition of the group selection content with the highest tag selection frequency among the group selection content for each classification condition.

[0128] When the extraction unit 43 extracts multiple comments posted by posting users with specific attributes for each period, the comment classification unit 44 classifies each of the multiple comments extracted by the extraction unit 43 for each period into a group that satisfies the classification criteria from among several groups.

[0129] The comment classification models described above include, for example, learning models generated by GBDT (Gradient Boosting Decision Tree) or learning models generated by deep learning using a deep neural network (DNN), but are not limited to such examples and may also be learning models generated by other machine learning methods.

[0130] [4.3.6. Specification part 45] The identification unit 45 identifies keywords for each comment group based on the text contained in the posted comments for each comment group.

[0131] The identification unit 45 has multiple keyword identification modes, and by using the keyword identification mode selected from among these multiple keyword identification modes, it is possible to identify keywords for each comment group.

[0132] For example, when the keyword identification mode is set to the first mode, the identification unit 45 extracts the most frequent word or phrase from the posted comments of the same group for each group, and identifies the extracted word or phrase for each group as the keyword for that group. The identification unit 45 can also identify two or more words or phrases in descending order of frequency as keywords for each group.

[0133] Furthermore, when the keyword identification mode is set to the second mode, the identification unit 45 can calculate the TF-IDF value of each word or phrase included in the comment for each group, and based on these TF-IDF values, extract characteristic words or phrases for each group as keywords for that group. The identification unit 45 can also identify two or more words or phrases as keywords for each group, in order of their TF-IDF values.

[0134] Furthermore, when the keyword identification mode is the third mode, the identification unit 45 identifies, for example, the user U who is the target of the provision of the target content in response to the content request. n Keywords for each group are identified based on specific conditions corresponding to the attributes of the recipient users. For example, the identification unit 45 has a keyword candidate table for each attribute of user U, and uses a keyword candidate table of a type corresponding to the attributes of the recipient users to identify keywords for each group.

[0135] Furthermore, when the keyword identification mode is the fourth mode, the identification unit 45 identifies, for example, the user U who is the target of the provision of the target content in response to the content request. n Based on specific conditions corresponding to the behavioral history of the recipient users, keywords are identified for each group. For example, the identification unit 45 has a keyword candidate table for each type of user U's behavior, and uses a keyword candidate table of the type corresponding to the behavioral history of the recipient users to identify keywords for each group.

[0136] For example, the identification unit 45 can select one of the first to fourth keyword identification modes based on the type of target content in response to a content request or the attributes of the recipient user, and use the selected keyword identification mode to identify keywords for each group.

[0137] Furthermore, the identification unit 45 can also identify keywords for each specific mode group using keywords other than those described above. Additionally, the keyword identification mode may be set to a mode specified by information from the submitter device 3 for each target content.

[0138] [4.3.7. Order Determination Section 46] The sorting order determination unit 46 determines the sorting order of attribute tags for each comment group identified by the identification unit 45. For example, the sorting order determination unit 46 determines the sorting order of attribute tags for each comment group based on at least one of the following: the evaluation of multiple posted comments within the comment group, the number of posted comments within the comment group, and the attributes of the recipient user.

[0139] Furthermore, the sorting order determination unit 46 prioritizes the attribute tags of comment groups with high ratings for multiple posts within the comment group, assigning them a higher position in the sorting order. For example, the rating for a post may be, for instance, a rating by users other than the user who posted the comment. For example, a comment group with many positive ratings for multiple posts within the comment group is considered a higher-rated comment group. The rating for a post may also be the ratio of positive ratings, for example, the ratio of positive ratings to negative ratings. In this case, for example, a post with a high proportion of positive ratings is considered a higher-rated post.

[0140] Furthermore, the sorting order determination unit 46 prioritizes the attribute tags of comment groups with a large number of posted comments, and determines their position in the sorting order to be higher.

[0141] Furthermore, the sorting order determination unit 46 can determine the sorting order of representative comments for each group based on the attributes of the recipient users. For example, the sorting order determination unit 46 prioritizes the position of attribute tags in the sorting order higher for comment groups that have many comments posted by posting users with attributes highly similar to those of the recipient users. For example, the sorting order determination unit 46 prioritizes the position of comments higher for comment groups that have a large number of comments posted by posting users with attributes highly similar to those of the recipient users. Attribute similarity is higher, for example, the more matching items there are or the higher the degree of matching, such as the user's gender, age, occupation, and location (or place of residence), but is not limited to these examples.

[0142] Furthermore, the sorting order determination unit 46 can also prioritize and determine the position of attribute tags in comment groups that have a large number of posts made by posting users with low attribute similarity to the recipient user.

[0143] [4.3.8.Providing Department 47] The provisioning unit 47 provides content corresponding to the request or information received by the receiving unit 41 to the requesting terminal device 2 by transmitting the content corresponding to the request or information to the requesting terminal device 2 and displaying it on the display unit 11 of the terminal device 2.

[0144] For example, when the receiving unit 41 receives a content list request, the providing unit 47 sends a list of content containing multiple target content of the type specified by the content list request to the requesting terminal device 2, and displays it on the display unit 11 of the terminal device 2, thereby providing the user U of the requesting terminal device 2 with a list of content corresponding to the content list request.

[0145] Figure 7 shows an example of list content provided by the information processing device 1 according to this embodiment. The list content 50 shown in Figure 7 includes a search box 51, a search button 52, a first content column 53, a tab column 54, a second content column 55, and a third content column 56.

[0146] The search box 51 receives a search keyword through an operation on the control unit 12 by the user U. When the search button 52 is selected by the user U through an operation on the control unit 12 while the search keyword is entered in the search box 51, the information output unit 18 of the terminal device 2 transmits a search query containing the search keyword entered in the search box 51 to an information providing device (not shown). This information providing device transmits search results corresponding to the search keyword included in the search query to the terminal device 2. These search results are acquired by the information acquisition unit 16 and displayed on the display unit 11 by the display processing unit 17.

[0147] Each piece of content in the first content column 53, the second content column 55, and the third content column 56 is content that, when selected by user U, will be moved to the destination content, and some of the content will, for example, display a portion of the information contained in the destination content.

[0148] When content in the first content column 53 is selected by user U, the content to which the selected content will be redirected is displayed in the display unit 11. User U can redisplay the list content 50 by selecting the back button or home button displayed in the display unit 11.

[0149] In the second content column 55, multiple target content items 57a, 57b, 57c, 57d, and 57e are arranged vertically. The multiple target content items 57a, 57b, 57c, 57d, and 57e arranged in the second content column 55 can be switched by selecting a tab in the tab column 54.

[0150] The third content column 56 includes home button content to transition to the initial screen, as well as content to transition to the destination content if selected by the user U. In the following, when target content 57a, 57b, 57c, 57d, and 57e are not individually distinguished, they may be referred to as target content 57.

[0151] When one of the multiple target contents 57 included in the second content column 55 is selected by user U through an operation on the operation unit 12, the information output unit 18 of the terminal device 2 transmits a content request to the information processing device 1, which includes information that identifies the target content 57 selected by user U.

[0152] The information processing device 1's provisioning unit 47 provides the content to user U by transmitting the requested content to the requesting terminal device 2 and displaying it on the display unit 11 of the terminal device 2.

[0153] The provided content includes target content corresponding to the content request, attribute selection content including tags for multiple attribute groups classified by the attribute classification unit 42, and comment content including multiple posted comments for the target content corresponding to the content request. Such provided content is an example of provided information.

[0154] Figure 8 shows an example of content provided by the provisioning unit 47 of the information processing device 1 according to this embodiment. The content provided 60 shown in Figure 8 includes target content 57 specified in the content request, comment content 61, attribute selection content 64, and a link 65. The link 65 is a GUI for returning to the list content 50 shown in Figure 7, and by selecting the link 65, user U can display the list content 50 on the terminal device 2. The content provided 60 is an example of provided information.

[0155] The comment content 61 includes posted comment information 62a and 62b corresponding to the target content 57 identified in the content request, and an additional display button 63. Each of the posted comment information 62a and 62b includes a posted comment 620, a positive rating button 621, a negative rating button 622, and a reply comment button 623.

[0156] Each comment 620 is a comment posted in response to the target content 57 identified in the content request. The positive rating button 621 is a GUI (Graphical User Interface) button that a user U who has viewed a comment 620 can select to give a positive rating to the comment 620, and the number of positive rating button 621 selections is indicated in the position corresponding to the positive rating button 621.

[0157] The negative rating button 622 is a GUI button that user U selects when they view comment 620 and want to give it a negative rating. The number of times the negative rating button 622 has been selected is displayed in a position corresponding to the negative rating button 622.

[0158] The reply comment button 623 is a GUI button for displaying comments in response to the posted comment 620. For example, if the number of comments in response to the posted comment 620 included in the posted comment information 62a is 43, then user U can display all 43 comments on the display unit 11 of the terminal device 2 by selecting the reply comment button 623 included in the posted comment information 62a.

[0159] The additional display button 63 displays commented comments for the target content 57 identified in the content request, other than the commented comment information 62a and 62b shown in the comment content 61. By selecting the additional display button 63, user U can display additional commented comment information other than the commented comment information 62a and 62b on the terminal device 2.

[0160] The attribute selection content 64 includes attribute tags 640, 641, 642, 643, 644, and 645 for each group corresponding to the target content 57 identified in the content request. Multiple posted comments for the target content 57 shown in Figure 8 are classified into multiple groups by the comment classification unit 44, and attribute tags 640, 641, 642, 643, 644, and 645 are tags for displaying comment content containing multiple posted comments classified into the corresponding group among the multiple groups classified by the comment classification unit 44 on the terminal device 2.

[0161] Attribute tag 640 is a tag used to display comment content containing multiple posts classified under the attribute group "men in their 30s" on terminal device 2. Attribute tag 641 is a tag used to display comment content containing multiple posts classified under the attribute group "women in their 30s" on terminal device 2. Attribute tag 642 is a tag used to display comment content containing multiple posts classified under the attribute group "men in their 40s" on terminal device 2.

[0162] Attribute tag 643 is a tag used to display comment content containing multiple posts classified under the attribute group "women in their 20s" on terminal device 2. Attribute tag 644 is a tag used to display comment content containing multiple posts classified under the attribute group "men in their 20s" on terminal device 2. Attribute tag 645 is a tag used to display comment content containing multiple posts classified under the attribute group "women in their 40s" on terminal device 2. User U can select one attribute tag from attribute tags 640, 641, 642, 643, 644, and 645, or select two or more attribute tags.

[0163] In the attribute selection content 64, attribute tags 640, 641, 642, 643, 644, and 645 are arranged in the order determined by the sorting determination unit 46. Of the attribute tags 640, 641, 642, 643, 644, and 645, attribute tag 640 is the highest rank, and attribute tags 641, 642, 643, 644, and 645 are one rank lower in that order.

[0164] In the example shown in Figure 8, the sizes of each attribute tag 640, 641, 642, 643, 644, and 645 are the same, but their sizes may be adjusted according to the number of posting users included in the corresponding attribute group. For example, the providing unit 47 can make each attribute tag 640, 641, 642, 643, 644, and 645 larger as the number of posting users included in the corresponding attribute group increases.

[0165] Furthermore, although the example shown in Figure 8 has six attribute tags, the system is not limited to this example. The providing unit 47 can, for example, include attribute tags of attribute groups in the attribute selection content 64 that have a number of classified posting users equal to or greater than a threshold among multiple attribute groups classified by the attribute classification unit 42. The providing unit 47 can also, for example, include attribute tags of a predetermined number of attribute groups in the attribute selection content 64 that have a number of classified posting users equal to or greater than a threshold among multiple attribute groups classified by the attribute classification unit 42.

[0166] When one of the multiple attribute tags 640, 641, 642, 643, 644, or 645 included in the attribute selection content 64 is selected by user U through an operation on the operation unit 12, the information output unit 18 of the terminal device 2 transmits selection information, including information that identifies the attribute tag selected by user U, to the information processing device 1.

[0167] If the selection information received by the reception unit 41 includes information to identify one of the attribute tags 640, 641, 642, 643, 644, or 645, the provision unit 47 transmits comment content, which includes multiple posted comments posted by multiple posting users classified into attribute groups corresponding to the attribute tag identified by the selection information among the attribute tags 640, 641, 642, 643, 644, or 645, to the terminal device 2 and displays it on the display unit 11 of the terminal device 2, thereby providing the comment content to user U.

[0168] Multiple posted comments, classified into attribute groups corresponding to attribute tags identified by the selection information received by the reception unit 41, are extracted by the comment classification unit 44. The attributes corresponding to the attribute tags identified by the selection information are examples of attributes specified by user U.

[0169] Figure 9 shows an example of comment content provided by the information processing device 1 according to the embodiment. The comment content 70 shown in Figure 9 includes posted comment information 71a, 71b, ..., classification information 72, and links 73. The posted comment information 71a, 71b, ... is information on posted comments posted by multiple posting users classified into attribute groups according to attribute tags identified by the selection information, and, like the posted comment information 62a, 62b, includes positive rating buttons, negative rating buttons, and reply comment buttons. Note that the posted comment information 71a, 71b, ... may also include a neutral rating button.

[0170] The classification information 72 includes information on attribute groups identified by the selection information and graph information. The graph information is a pie chart showing the number of posted comments classified into each comment group of the attribute group identified by the selection information, and the graph shows the keywords for each comment group identified by the identification section 45 as the content for each comment group. The attribute group information identified by the selection information is an example of information on a specific attribute.

[0171] The classification information 72 shown in Figure 9 includes a graph that shows the number of posts classified into each of three comment groups, into which multiple posts made by a male user in his 30s have been classified.

[0172] The classification information 72 shown in Figure 9 includes the keywords "good" and "new," "bad" and "useless," and "meaningless" and "neither" as keywords for each comment group identified by the identification unit 45. The keywords for each comment group are an example of information that indicates the content of each comment group. Note that the information indicating the content of each comment group in the classification information 72 may also be information such as strings that are pre-associated with the comment groups.

[0173] Furthermore, in the example shown in Figure 9, the pie chart indicated by classification information 72 is a pie chart that shows the number of comments classified into each comment group as a percentage, such as 38%, 32%, and 30%. However, it may also be a pie chart that shows the number of comments classified into each comment group as a value.

[0174] Furthermore, the classification information 72 shown in Figure 9 includes pie chart information showing the number of comments classified into each comment group as graph information, but the graph information may also be bar graphs or donut charts showing the number of comments classified into groups.

[0175] The providing unit 47 can, for example, provide graph information included in the classification information 72 in a format corresponding to an attribute group (an example of a specific attribute) identified by the selection information. For example, the providing unit 47 can provide classification information 72 that includes graph information in a format corresponding to an attribute group, selected from among multiple graph formats including pie charts, bar graphs, and donut charts.

[0176] Furthermore, the providing unit 47 can make the graph included in the classification information 72 a pie chart if the number of comment groups of the attribute group identified by the selection information is less than a threshold, and a bar graph if the number of comment groups of the attribute group identified by the selection information is equal to or greater than the threshold.

[0177] Furthermore, the providing unit 47 can also determine the format of the graph included in the classification information 72 based on the group type of the attribute group identified by the selection information and the number of comment groups of the attribute group identified by the selection information.

[0178] Link 73 is a GUI for returning to the provided content 60 shown in Figure 8, and by selecting Link 73, user U can display the provided content 60 on terminal device 2.

[0179] The content provided by the provisioning unit 47 is not limited to the examples described above. Figure 10 shows another example of comment content provided by the provisioning unit 47 of the information processing device 1 according to the embodiment.

[0180] The provisioning unit 47 can provide user U with comment content 70 including classification information 72 as shown in Figure 10, instead of comment content 70 including classification information 72 as shown in Figure 9. The classification information 72 of the comment content 70 shown in Figure 10 is information showing the changes in the results classified by the comment classification unit 44 over multiple periods, and includes multiple classification information 74a, 74b, and 74c.

[0181] Each of the classification information items 74a, 74b, and 74c contains pie chart information showing the number of posted comments classified into each comment group of the attribute group identified in the selection information. The classification information items 74a, 74b, and 74c are pie chart information showing the number of comments classified into each comment group of the attribute group identified in the selection information over different time periods.

[0182] In the classification information 72 shown in Figure 10, classification information 74a is pie chart information of posted comments made up to 24 hours ago, classification information 74b is pie chart information of posted comments made more than 1 day ago, and classification information 74c is pie chart information of posted comments made over the entire period.

[0183] Furthermore, the classification change information, which shows the changes in the results classified by the comment classification unit 44 over multiple periods, is not limited to the pie chart information shown in Figure 10. For example, it may also be bar graph information that includes a color-coded figure (for example, a rectangular figure color-coded according to the number of comments included in each comment group) for each period, showing the results classified by the comment classification unit 44. Alternatively, the classification change information may also be line graph information that connects the number of comments included in each comment group for each period.

[0184] Furthermore, in the example described above, the providing unit 47 provides the providing content 60 which includes the attribute selection content 64, but it is also possible to provide the providing content 60 which includes a recommendation button instead of the attribute selection content 64.

[0185] The information output unit 18 of the terminal device 2 transmits information to the information processing device 1 as selection information to identify the recommendation button when user U selects a recommendation button included in the provided content 60. If the selection information received by the receiving unit 41 includes information to identify the recommendation button, the providing unit 47 can provide comment content 70 corresponding to multiple posted comments extracted by the extraction unit 43 as specific attributes that match or are similar to the attributes of the recipient user.

[0186] For example, suppose the attribute that matches or is similar to the attribute of the recipient user is that the user is a man in his 40s. In this case, the provisioning unit 47 provides comment content 70 that includes, as classification information, information about a graph showing the number of posted comments classified into each comment group of the attribute group of men in their 40s, and the keywords for each comment group identified by the identification unit 45 as the content for each posted comment group.

[0187] [5. Processing Procedure] Next, the procedure for information processing by the processing unit 22 of the information processing device 1 according to the embodiment will be described. Figure 11 is a flowchart showing an example of information processing by the processing unit 22 of the information processing device 1 according to the embodiment.

[0188] As shown in Figure 11, the processing unit 22 of the information processing device 1 determines whether or not the target content has been submitted from the submitter device 3 (step S20). If the processing unit 22 determines that the target content has been submitted (step S20: Yes), it stores the submitted target content in the storage unit 21 (step S21).

[0189] If the processing in step S21 is completed, or if it is determined that no target content has been submitted (step S20: No), the processing unit 22 determines whether or not there are any submitted comments (step S22). If the processing unit 22 determines that there are submitted comments (step S22: Yes), it stores the submitted comments in the storage unit 21 (step S23).

[0190] If the processing in step S23 is completed, or if it is determined that no comments have been posted (step S22: No), the processing unit 22 determines whether it is time for classification (step S24). For example, the processing unit 22 determines that it is time for classification if a content request is received or a comment has been posted.

[0191] If the processing unit 22 determines that it is time for classification (step S24: Yes), it classifies multiple posting users into multiple attribute groups for each target content (step S25). Then, the processing unit 22 classifies multiple posted comments for the target content into multiple comment groups for each target content and attribute group (step S26). The processing unit 22 also identifies keywords for each comment group and determines the order of keywords for each attribute group within each comment group (step S27).

[0192] If the processing in step S27 is completed, or if it is determined that it is not time for classification (step S24: No), the processing unit 22 determines whether or not it has received a content request or selection information (step S28). If the processing unit 22 determines that it has received a content request or selection information (step S28: Yes), it provides content corresponding to the content request or selection information to user U by sending the content corresponding to the content request or selection information to the terminal device 2 and displaying it on the terminal device 2 (step S29).

[0193] When the processing in step S29 is completed, or when it is determined that no content request or selection information has been received (step S28: No), the processing unit 22 determines whether it is time to terminate the operation (step S30). For example, the processing unit 22 determines that it is time to terminate the operation when the power to the information processing device 1 is turned off, or when it is determined that a termination operation has been performed by operating on an unillustrated control unit of the information processing device 1.

[0194] If the processing unit 22 determines that it is not yet time to terminate the operation (step S30: No), it proceeds to step S20. If it determines that it is time to terminate the operation (step S30: Yes), it terminates the process shown in Figure 11.

[0195] [6. Variant Example] In the example described above, the online services provided by the information processing device 1 are, but are not limited to, online services such as news sites, shopping sites, auction sites, flea market sites, restaurant review sites, review sites, and social networking sites. The information processing device 1 may also provide online services such as map provision sites, travel sites, and search sites.

[0196] Furthermore, the terminal device 2 can work in conjunction with the information processing device 1 to execute some or all of the functions of one or more of the following: acquisition unit 40, reception unit 41, attribute classification unit 42, extraction unit 43, comment classification unit 44, identification unit 45, sorting order determination unit 46, and provision unit 47. It can also function as part of an information processing device having some or all of the functions of one or more of the following: acquisition unit 40, reception unit 41, attribute classification unit 42, extraction unit 43, comment classification unit 44, identification unit 45, sorting order determination unit 46, and provision unit 47. In the following, the configuration including some or all of the above-described information processing device 1 and terminal device 2 may be referred to as the information processing device 1.

[0197] The processing unit 15 shown in Figure 3 is realized, for example, by a processor such as a CPU or MPU executing various programs (an example of an information processing program) stored in a memory device (for example, a memory unit 14) inside the terminal device 2, using RAM as the working area.

[0198] [7. Hardware Configuration] The information processing device 1 or terminal device 2 according to the above embodiment is implemented by a computer 80 having a configuration such as that shown in Figure 12. The following explanation will use the information processing device 1 as an example. Figure 12 is a hardware configuration diagram showing an example of a computer 80 that implements the functions of the information processing device 1 according to the embodiment. The computer 80 has a CPU 81, RAM 82, ROM (Read Only Memory) 83, HDD (Hard Disk Drive) 84, communication interface (I / F) 85, input / output interface (I / F) 86, and media interface (I / F) 87.

[0199] The CPU 81 operates based on programs stored in the ROM 83 or HDD 84, and controls various parts of the system. The ROM 83 stores boot programs executed by the CPU 81 when the computer 80 starts up, as well as programs that depend on the computer 80's hardware.

[0200] HDD84 stores programs executed by CPU81 and data used by such programs. The communication interface85 receives data from other devices via network N (see Figure 2) and sends it to CPU81, and transmits data generated by CPU81 to other devices via network N.

[0201] The CPU 81 controls output devices such as displays and printers, and input devices such as keyboards and mice, via the input / output interface 86. The CPU 81 acquires data from input devices via the input / output interface 86. The CPU 81 also outputs data it has generated to output devices via the input / output interface 86.

[0202] The media interface 87 reads a program or data stored in the recording medium 88 and provides it to the CPU 81 via the RAM 82. The CPU 81 loads the program from the recording medium 88 onto the RAM 82 via the media interface 87 and executes the loaded program. The recording medium 88 can be, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or 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.

[0203] For example, when the computer 80 functions as an information processing device 1 according to the embodiment, the CPU 81 of the computer 80 realizes the functions of the processing unit 22 by executing a program loaded on the RAM 82. The HDD 84 stores data from the storage unit 21. The CPU 81 of the computer 80 reads and executes these programs from the recording medium 88, but as another example, these programs may be obtained from other devices via a network N.

[0204] [8. Other] Furthermore, some of the processes described as being performed automatically in the above embodiments can be performed manually. Alternatively, all or part of the processes described as being performed manually can be performed automatically by known methods. In addition, the processing procedures, specific names, and various data and parameters shown in the above documents and drawings can be changed at will unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown.

[0205] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions.

[0206] For example, the information processing device 1 described above may be implemented using multiple server computers, and the configuration can be flexibly changed, such as by calling external platforms via APIs or network computing depending on the function. Also, some of the processing of the information processing device 1 described above may be handled by the terminal device 2. In this case, some functions of the terminal device 2 will function as an information processing device together with the information processing device 1.

[0207] Furthermore, for example, some or all of the storage unit 21 shown in Figure 4 may be stored in a storage server or the like, rather than being held by each device. In this case, each device obtains various information by accessing the storage server.

[0208] [9. Effects] As described above, the information processing device 1 according to this embodiment comprises an extraction unit 43, a comment classification unit 44, and a provision unit 47. The extraction unit 43 extracts multiple comments posted by users with specific attributes from among multiple comments posted on content. The comment classification unit 44 classifies each of the multiple comments extracted by the extraction unit 43 into a comment group that satisfies classification conditions from among multiple comment groups. The provision unit 47 provides provision information including classification information that shows the results of the classification by the comment classification unit 44. This makes it easy for the information processing device 1 to view comments.

[0209] Furthermore, the classification criteria are conditions related to the content of the comments, and the comment classification unit 44 classifies each of the multiple comments into a comment group according to its content. This makes it even easier for the information processing device 1 to view comments.

[0210] Furthermore, the classification criteria are conditions related to the user's activity history when posting a comment, and the comment classification unit 44 classifies each of the multiple comments into a comment group according to the user's activity history. This makes it even easier for the information processing device 1 to view comments.

[0211] Furthermore, the classification criteria are conditions related to the posting date and time of the comments, and the comment classification unit 44 classifies each of the multiple comments into a comment group according to the posting date and time. This makes it even easier for the information processing device 1 to view comments.

[0212] Furthermore, the information provision unit 47 provides, as classification information, graph information showing the number of comments classified into each comment group. This makes it even easier for the information processing device 1 to view comments.

[0213] Furthermore, the information provider 47 provides pie chart information showing the number of comments classified into each comment group as graph information. This makes it even easier for the information processing device 1 to view comments.

[0214] Furthermore, the information provision unit 47 provides classification information, including the number of comments classified into each comment group, as well as graph information showing the content of each comment group. This makes it even easier for the information processing device 1 to view comments.

[0215] Furthermore, the information processing device 1 includes an identification unit 45 that identifies keywords for each comment group based on the text contained in the comments for each comment group. The providing unit 47 provides graph information that shows the keywords for each comment group identified by the identification unit as the content for each comment group. This makes it even easier for the information processing device 1 to view comments.

[0216] Furthermore, the providing unit 47 provides information that includes information indicating specific attributes as providing information. This makes it even easier for the information processing device 1 to view comments.

[0217] Furthermore, the data provision unit 47 provides graph information in a format corresponding to specific attributes as classification information. This makes it even easier for the information processing device 1 to view comments.

[0218] Furthermore, the extraction unit 43 extracts multiple comments by specifying attributes that match or are similar to the user attributes for which classification information is provided. This makes it even easier for the information processing device 1 to view comments.

[0219] Furthermore, the extraction unit 43 extracts multiple comments using the attribute specified by the user for which classification information is provided as a specific attribute. This makes it even easier for the information processing device 1 to view the comments.

[0220] Furthermore, the extraction unit 43 extracts multiple comments posted during each of multiple periods, the comment classification unit 44 classifies each of the multiple comments extracted by the extraction unit for each period into a comment group that satisfies the classification criteria from among multiple comment groups, and the provision unit 47 provides information as classification information, showing the changes in the results classified by the comment classification unit over multiple periods. This makes it even easier for the information processing device 1 to view comments.

[0221] Although embodiments of the present application have been described in detail based on the drawings, these are illustrative examples, and the present invention can be implemented in various other forms, including those described in the disclosure section of the invention, based on the knowledge of those skilled in the art.

[0222] Furthermore, the terms "section, module, unit" mentioned above can be replaced with "means" or "circuit," etc. For example, the acquisition unit can be replaced with acquisition means or acquisition circuit. [Explanation of Symbols]

[0223] 1. Information Processing Device 2,21~2 n Terminal device 3,31~3 m Submitter's device 10,20 Communications Department 11 Display section 12 Control section 13 Sensor Groups 14,21 Storage part 15,22 Processing Unit 16 Information acquisition department 17 Display Processing Unit 18. Information Output Unit 30 User information storage unit 31 Content storage unit 40 Acquisition Department 41 Reception Department 42 Attribute classification section 43 Extraction part 44 Comment Classification Section 45 Specific part 46. ​​Order Determination Section 47 Providing Department 100 Information Processing Systems N Network

Claims

1. An extraction unit that extracts from among multiple comments posted on news content the comments posted by a user who has a specific attribute, which is an attribute identified by an attribute tag selected by the user to whom the provided information is available, from among multiple attribute tags that each identify one or more of the following: age, gender, occupation, place of residence, annual income, and family structure. A comment classification unit that classifies each of the multiple comments extracted by the extraction unit into a group that satisfies the classification criteria from among multiple groups, The system includes a providing unit that provides providing information including classification information showing the results of classification by the comment classification unit, The aforementioned multiple attribute tags are, In the provided content, including the aforementioned news content, attribute tags with a higher number of users posting to the news content will be placed higher in the sorting order. An information processing device characterized by the following:

2. The aforementioned classification criteria are: These are conditions related to the content of the aforementioned comments, The aforementioned comment classification unit is, Each of the aforementioned comments is classified into a group according to its content. The information processing apparatus according to feature 1.

3. The aforementioned classification criteria are: These are conditions related to the user's activity history when posting the aforementioned comment. The aforementioned comment classification unit is, Each of the aforementioned comments is classified into a group corresponding to the posting user's activity history. The information processing apparatus according to feature 1.

4. The aforementioned classification criteria are: This is a condition regarding the posting date and time of the aforementioned comment. The aforementioned comment classification unit is, Each of the aforementioned comments is classified into a group corresponding to the posting date and time. The information processing apparatus according to feature 1.

5. The aforementioned supply unit is, The classification information provided includes a graph showing the number of comments classified into each group. The information processing apparatus according to any one of claims 1 to 4.

6. The aforementioned supply unit is, Information from a pie chart showing the number of comments classified into each of the aforementioned groups is provided as information for the graph. The information processing apparatus according to feature 5.

7. The aforementioned supply unit is, The classification information includes the number of comments classified into each group, as well as graph information showing the content of each group. The information processing apparatus according to feature 5.

8. The system includes a special unit that identifies keywords for each group based on the text contained in the comments for each group, The aforementioned supply unit is, The graph provides information showing the keywords for each group identified by the specified unit as content for each group. The information processing apparatus according to feature 6.

9. The aforementioned supply unit is, The information of a graph in a format corresponding to the specified attribute is provided as the classification information. The information processing apparatus according to any one of claims 1 to 4.

10. The extraction unit is The multiple comments are extracted using the attributes that match or are similar to the user attributes for which the classification information is provided as the specific attributes. The information processing apparatus according to any one of claims 1 to 4.

11. The extraction unit is The user specified by the classification information is used to extract the multiple comments, with the attribute specified by the user being used as the specific attribute. The information processing apparatus according to any one of claims 1 to 4.

12. The extraction unit is Multiple comments posted during each of the multiple periods are extracted for each of the aforementioned periods. The aforementioned comment classification unit is, Each of the multiple comments extracted by the extraction unit for each period is classified for each period into one of the multiple groups that satisfies the classification criteria. The aforementioned supply unit is, The classification information provided includes information showing the changes in the results classified by the comment classification unit over the aforementioned multiple periods. The information processing apparatus according to any one of claims 1 to 4.

13. A method of information processing performed by a computer, An extraction process for extracting multiple comments posted on news content that were posted by users who possess a specific attribute identified by an attribute tag selected by the user to whom the information is provided, from among multiple attribute tags that each identify one or more of the following: age, gender, occupation, place of residence, annual income, and family structure. A comment classification step in which each of the multiple comments extracted by the extraction step is classified into a group that satisfies the classification criteria from among multiple groups, A provisioning step includes providing information that includes classification information showing the results of the comment classification step, The aforementioned multiple attribute tags are, In the provided content, including the aforementioned news content, attribute tags with a higher number of users posting to the news content will be placed higher in the sorting order. An information processing method characterized by the following:

14. An extraction procedure for extracting multiple comments posted on news content, in which the comments are posted by a user who has a specific attribute, which is identified by an attribute tag selected by the user to whom the provided information is available, from among multiple attribute tags that each identify one or more of the following: age, gender, occupation, place of residence, annual income, and family structure. A comment classification procedure that classifies each of the multiple comments extracted by the extraction procedure into a group that satisfies the classification criteria from among multiple groups, A provisioning procedure is performed on a computer to provide information including classification information showing the results of the comment classification procedure described above. The aforementioned multiple attribute tags are, In the provided content, including the aforementioned news content, attribute tags with a higher number of users posting to the news content will be placed higher in the sorting order. An information processing program characterized by the following features.

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