Information processing apparatus, information processing method, and information processing program

Abstract

To provide a device, a method and a program for visualizing the divergence of opinions to the same event due to the difference of media.SOLUTION: The server device includes an extracting unit that extracts an information group posted on a predetermined event for each of an information group posted on a first medium and an information group posted on a second medium, a comparing unit that compares directivities of opinions of the information groups posted on the first medium and the second medium for the predetermined event, and a presenting unit that presents content in which a divergence between the directivities of the opinions of the information groups posted on the first medium and the second medium is visualized. terminal.SELECTED DRAWING: Figure 3

Description

[Technical Field]

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

[0002] A technology has been disclosed for delivering image information related to the contents of an electronic article to a user terminal (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2023-072949 Summary of the Invention [Problem to be solved by the invention]

[0004] However, while the above-mentioned conventional technology can create a multi-line summary of the content of an article from the main text of the article contained in an electronic article, it is not possible to determine the nature of the discrepancy when there is a discrepancy in opinions between posts on social media and posts on news articles about the same event. Therefore, there is a need for a means to visualize the discrepancy in opinions about the same event depending on the medium.

[0005] The present application has been made in light of the above, and aims to visualize the divergence of opinions on the same event due to differences in media. [Means for solving the problem]

[0006] The information processing device of the present application is characterized by comprising an extraction unit that extracts a group of information posted regarding a specified event from each of a group of information posted on a first medium and a group of information posted on a second medium; a comparison unit that compares the direction of opinions of the group of information posted on the first medium and the second medium regarding the specified event; and a presentation unit that presents content that visualizes the divergence in the direction of opinions of the group of information posted on the first medium and the second medium. [Effects of the Invention]

[0007] According to one aspect of the embodiment, it is possible to visualize the difference in opinions about the same event due to different media. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is an explanatory diagram showing an overview of an information processing system according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the configuration of a terminal device according to the embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of the configuration of a server device according to the embodiment. [Figure 4] FIG. 4 is a flowchart showing a processing procedure according to the embodiment. [Figure 5] FIG. 5 is a diagram illustrating an example of a hardware configuration. DETAILED DESCRIPTION OF THE INVENTION

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

[0010] [1. Overview of the information processing system] First, an overview of an information processing system according to an embodiment will be described with reference to Fig. 1. Fig. 1 is an explanatory diagram showing an overview of an information processing system according to an embodiment. As shown in Fig. 1, an information processing system 1 according to an embodiment includes a terminal device 10 and a server device 100. The terminal device 10 and the server device 100 are connected to each other via a network N in a wired or wireless manner so as to be able to communicate with each other. This enables the terminal device 10 to cooperate with the server device 100. The network N is, for example, a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, etc.

[0011] Terminal device 10 is an information processing device used by a user U. For example, terminal device 10 may be a smart device such as a smartphone or tablet terminal, a desktop or notebook (laptop) type PC (Personal Computer), a mobile phone such as a feature phone (Gala-ke or Gala-ho), a PDA (Personal Digital Assistant), a game console or AV device with communication functions, an information appliance or digital appliance, a car navigation system, a wearable device such as a smart watch, a head-mounted display, or smart glasses. Terminal device 10 may also be a house or building, a car, a home appliance, an electronic device, or the like that is compatible with the Internet of Things (IOT).

[0012] In this embodiment, the terminal device 10 is a smart device such as a smartphone or tablet used by a user U, and is a portable terminal device capable of communicating with any server device via a wireless communication network such as LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation: fifth generation mobile communication system), Bluetooth (registered trademark), or wireless LAN. The terminal device 10 has a screen such as a liquid crystal display with a touch panel function, and accepts various operations on displayed data such as content, such as tapping, sliding, and scrolling, performed by the user U with a finger or a stylus. An operation performed on an area of ​​the screen where content is displayed may be considered an operation on the content. The terminal device 10 may be not only a smart device, but also an information processing device such as a desktop PC or a laptop PC.

[0013] The server device 100 is, for example, a computer such as a PC or a blade server, or a mainframe or a workstation, etc. The server device 100 may be realized by cloud computing.

[0014] In this embodiment, the server device 100 is an information processing device that works in conjunction with the terminal device 10 of each user U and provides API (Application Programming Interface) services for various applications (hereinafter referred to as apps) and various data to the terminal device 10 of each user U, and is realized by a computer, a cloud system, etc.

[0015] The server device 100 may also be an information processing device that provides some kind of online service to the terminal device 10 of each user U. For example, the server device 100 may provide the following online services: internet connection, search service, chat service, interactive service using voice, images, videos, etc., social networking service (SNS), electronic commerce (EC), electronic payment, online games, online banking, online trading, hotel and ticket reservations, video and music distribution, news, maps, route search, route guidance, line information, operation information, weather forecast, etc. In practice, the server device 100 may cooperate with various servers that provide the above-mentioned online services and act as an intermediary for the online services or may be responsible for processing the online services.

[0016] The server device 100 can acquire user information about the user U. For example, the server device 100 acquires, as the user information, information (attribute information) about the attributes of the user U, such as the gender, age, and residential area of ​​the user U. The server device 100 can also acquire information about the attributes of the user U, such as demographic attributes, psychographic attributes, geographic attributes, and behavioral attributes. The server device 100 may also acquire, as the user information, a segment to which the user U belongs in the marketing field or a persona (personality). The server device 100 then stores and manages the information (attribute information) about the attributes of the user U together with identification information (such as a user ID) that identifies the user U.

[0017] The server device 100 also acquires various types of history information (log data) indicating the behavior of the user U from the terminal device 10 of the user U or from various servers based on the user ID, etc. For example, the server device 100 acquires a location history, which is a history of the user U's location and date and time, from the terminal device 10. The server device 100 also acquires a search history, which is a history of search queries entered by the user U, from a search server (search engine). The server device 100 also acquires a browsing history, which is a history of content viewed by the user U, from a content server. The server device 100 also acquires a purchase history (payment history), which is a history of the user U's product purchases and payment processes, from an e-commerce server or a payment processing server. The server device 100 may also acquire a listing history and a sales history, which are a history of the user U's listings on the marketplace, from the e-commerce server or the payment processing server. The server device 100 also acquires a posting history, which is a history of the user U's posts, from a posting server or SNS server that provides a word-of-mouth posting service. The various servers and the like described above may be the server device 100 itself. That is, the server device 100 may function as the various servers and the like described above.

[0018] Furthermore, the number of devices included in the information processing system 1 shown in Fig. 1 is not limited to that shown in the figure. For example, in Fig. 1, for the sake of simplicity, only one terminal device 10 is shown, but this is merely an example and is not limiting, and two or more devices may be included.

[0019] [2. Visualizing the difference in opinions on the same issue due to differences in media] In this embodiment, the server device 100 visualizes the difference in opinions about the same event due to differences in media and platforms. For example, the server device 100 finds and visualizes events and content for which there is a large difference in opinions between SNS and news sites / apps. Specifically, the server device 100 compares the content of posts that are ranked highly on SNS using a real-time search with the content of comments posted on news about similar topics, and visualizes the difference and the key points for each platform.

[0020] The server device 100 realizes the above mechanism using AI (Artificial Intelligence) such as GPT (Generative Pre-trained Transformer). GPT is a text generation AI, and is a language model capable of generating sentences using natural language processing. However, AI such as GPT is merely an example. In reality, a similar technology may also be used.

[0021] For example, as shown in FIG. 1A, the server device 100 estimates a major event based on the amount of articles, the number of views or comments, or ranking order, etc. (step S1).

[0022] For example, the server device 100 estimates that the event that is the subject of the news article with the most views (or comments) among the news articles on a news site / app is a major event. Alternatively, the server device 100 references a list of topics on the news site / app to determine whether or not major news that will become a public topic has occurred. In this case, if the list of topics on the news site / app contains a predetermined number or more (e.g., three or more) of topics related to the same news, or if a predetermined number or more comments have been posted on the estimated topic within a certain period of time (if the number of posted comments has increased sharply), the server device 100 estimates that major news that will become a public topic has occurred, and estimates the event that is the subject of the news as a major event.

[0023] Alternatively, the server device 100 estimates, as a major event, an event that is the subject of a post that is ranked highly on the SNS in a real-time search. For example, the server device 100 estimates, as a major event, an event that is a topic of discussion in posts that are ranked within a predetermined order (for example, within the top 100) on the SNS.

[0024] In practice, the server device 100 may estimate not only major events but also common events that are topics of discussion in both SNS posts and news articles. For example, the server device 100 may estimate events that are included in both the content of a post that ranks highly on SNS and the content of a topic in a list of topics on a news site / app. However, the above is merely an example. In practice, the present invention is not limited to the above example.

[0025] Next, the server device 100 extracts posts related to the event from among posts on the SNS (step S2). Next, the server device 100 extracts news articles related to the event from among news articles on news sites / apps (step S3).

[0026] For example, the server device 100 extracts posts on the SNS that feature the event or posts that include the event in their content. The server device 100 also extracts news articles on a news site / app that feature the event or news articles that include the event in their content.

[0027] In addition, the process of extracting posts related to the event in step S2 above and the process of extracting news articles related to the event in step S3 above may be performed simultaneously or in parallel with step S1 above, or within the processing of step S1 above.

[0028] Next, the server device 100 classifies the SNS posts and the comments on the news article that are about the same event into predetermined categories (step S4).

[0029] For example, if the event is the "Tokyo gubernatorial election," the server device 100 classifies the event into categories such as "election coverage," "candidate XX," "candidate XX," "campaign promises," and "policies." In other words, the server device 100 classifies each of the SNS posts and comments on news articles that are based on the same event into one of multiple predetermined categories. Note that, if the content of one SNS post (or comment) contains content from multiple categories, the server device 100 may separate and classify the content by category, or may classify one SNS post (or comment) into multiple categories.

[0030] Next, the server device 100 summarizes the main points of each of the SNS posts and the comments on the news articles by the classified items (step S5).

[0031] For example, the server device 100 aggregates and summarizes SNS posts related to the same topic to summarize the main points. Similarly, the server device 100 aggregates and summarizes the contents of comments related to the same topic to summarize the main points.

[0032] Next, the server device 100 extracts and compares key points for each item of the SNS post and the comment on the news article, and determines, as a result of the comparison, items for which there is a large discrepancy between the key points of the SNS post and the key points of the comment content (step S6).

[0033] For example, the server device 100 calculates the degree of discrepancy between the main points of the SNS post and the main points of the comment content, and determines that the discrepancy is large if the degree of discrepancy is equal to or greater than a threshold. Alternatively, the server device 100 calculates the similarity between the main points of the SNS post and the main points of the comment content, and determines that the discrepancy is small (not large) if the similarity is equal to or greater than a threshold. The degree of discrepancy or similarity between the main points may be calculated using a technique such as natural language processing (NLP). For example, the server device 100 may vectorize the main points of the SNS post and the main points of the comment content, and calculate the discrepancy or similarity from the cosine similarity of the multidimensional vectors. However, the above is merely an example. In practice, the present invention is not limited to the above example.

[0034] Next, the server device 100 classifies, for each of the SNS post and the comment on the news article, items that have a large discrepancy between the main points of the SNS post and the main points of the comment content into "positive," "negative," or "neutral" (step S7).

[0035] For example, for each of the SNS post and the comment on the news article, the server device 100 estimates whether the item with the largest discrepancy between the main points of the SNS post and the main points of the comment content corresponds to "positive," "negative," or "neutral."

[0036] Next, the server device 100 presents a table that classifies items with large discrepancies into "positive," "negative," or "neutral" based on the estimated results for each of the SNS posts and the comments on the news article, and also presents a written summary of the overall trend (step S8).

[0037] For example, the server device 100 generates a table classifying the direction of opinions into "positive," "negative," or "neutral" for each of SNS posts and comments on news articles, and generates content including a written description of the overall direction of opinions, and presents this to the user U.

[0038] The above example is a pattern in which the items are determined in advance. In the case of a pattern in which the items are automatically set, it will be as follows:

[0039] For example, as shown in FIG. 1B, the server device 100 estimates a major event based on the amount of articles, the number of views or comments, or ranking order, etc. (Step S1). Alternatively, the server device 100 estimates an event common to SNS posts and news articles. Next, the server device 100 extracts posts related to the event from the SNS posts (Step S2). Next, the server device 100 extracts news articles related to the event from news articles on news sites / apps (Step S3). Steps S1 to S3 are the same as those in FIG. 1A above.

[0040] Next, the server device 100 classifies the SNS posts and the comments on the news articles that are related to the same event based on common or similar content (step S4A).

[0041] For example, the server device 100 groups together SNS posts with common or similar content in terms of assertion or tone as SNS posts of the same category. Similarly, the server device 100 groups together comments with common or similar content in terms of assertion or tone as comments of the same category.

[0042] Note that common or similar content may be determined using techniques such as natural language processing (NLP). For example, the server device 100 may vectorize the main points of the SNS posts and the main points of the comment content, and determine the commonality or similarity of the content from the cosine similarity of the multidimensional vectors. However, the above is merely an example. In practice, the present invention is not limited to the above example.

[0043] Next, the server device 100 sets items for each of the classified SNS posts and comments on the news articles based on the classified contents (step S4B).

[0044] For example, if the event is "substitution of athletes in a game," the server device 100 sets "athletes," "rules," and the like as the items.

[0045] Next, the server device 100 summarizes the main points of each of the SNS posts and the comments on the news article for each item (step S5). Next, the server device 100 extracts and compares the main points of each of the SNS posts and the comments on the news article, and determines, based on the comparison results, items for which the main points of the SNS posts and the comments on the news article differ significantly (step S6). When the main points of the SNS posts and the comments on the news article are compared for each item, items for which the comparison results are dissimilar are identified. Next, the server device 100 estimates whether the items for each of the SNS posts and the comments on the news article that differ significantly from the main points of the SNS posts and the comments on the news article fall into one of "positive," "negative," or "neutral" categories (step S7). Next, the server device 100 presents a table in which the items for each of the SNS posts and the comments on the news article that differ significantly are classified into "positive," "negative," or "neutral" based on the estimation results, and also presents a written summary of the overall trend (step S8). Steps S5 to S8 are the same as those in FIG. 1(A) above.

[0046] As described above, in this embodiment, the server device 100 acquires a group of information posted in a first domain (first medium) and a group of information posted in a second domain (second medium) regarding a predetermined event. The server device 100 then generates and provides content that compares the direction of opinions in the group of information posted in the first domain and the second domain. This visualizes events in which a divergence of opinions occurs between SNS and news comments.

[0047] [3. Example of terminal device configuration] Next, the configuration of the terminal device 10 will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of the configuration of the terminal device 10 according to the embodiment. As shown in Fig. 2, the terminal device 10 includes a communication unit 11, a display unit 12, an input unit 13, a positioning unit 14, a sensor unit 20, a control unit 30 (controller), and a storage unit 40.

[0048] (Communications Department 11) The communication unit 11 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the server device 100 via the network N. For example, the communication unit 11 is realized by a NIC (Network Interface Card), an antenna, etc.

[0049] (Display section 12) Display unit 12 is a display device that displays various information such as position information. For example, display unit 12 is a liquid crystal display (LCD) or an organic electro-luminescent display (OLED). Display unit 12 is also a touch panel display, but is not limited to this.

[0050] (Input section 13) The input unit 13 is an input device that accepts various operations from the user U. For example, the input unit 13 has buttons for inputting characters, numbers, etc. The input unit 13 may be an input / output port (I / O port), a USB (Universal Serial Bus) port, etc. If the display unit 12 is a touch panel display, a part of the display unit 12 functions as the input unit 13. The input unit 13 may be a microphone that accepts voice input from the user U. The microphone may be wireless.

[0051] (Positioning unit 14) The positioning unit 14 receives signals (radio waves) transmitted from satellites of a GPS (Global Positioning System), and acquires position information (e.g., latitude and longitude) indicating the current position of the terminal device 10, which is the device itself, based on the received signals. That is, the positioning unit 14 positions the position of the terminal device 10. Note that GPS is merely an example of a GNSS (Global Navigation Satellite System).

[0052] The positioning unit 14 can also measure the position using various methods other than GPS. For example, the positioning unit 14 may measure the position by using various communication functions of the terminal device 10 as an auxiliary positioning means for position correction, etc., as described below.

[0053] (Wi-Fi positioning) For example, the positioning unit 14 uses a Wi-Fi (registered trademark) communication function of the terminal device 10 or a communication network provided by each communication company to measure the position of the terminal device 10. Specifically, the positioning unit 14 performs Wi-Fi communication or the like and measures the distance to a nearby base station or access point, thereby measuring the position of the terminal device 10.

[0054] (Beacon positioning) The positioning unit 14 may also measure the position by using a Bluetooth (registered trademark) function of the terminal device 10. For example, the positioning unit 14 measures the position of the terminal device 10 by connecting to a beacon transmitter connected by the Bluetooth (registered trademark) function.

[0055] (geomagnetic positioning) The positioning unit 14 also measures the position of the terminal device 10 based on a geomagnetic pattern of a structure that has been measured in advance and a geomagnetic sensor that the terminal device 10 has.

[0056] (RFID positioning) Furthermore, for example, if the terminal device 10 has a function of an RFID (Radio Frequency Identification) tag equivalent to a contactless IC card used at station ticket gates, in stores, etc., or has a function of reading an RFID tag, the location where the terminal device 10 was used is recorded together with information on the payment or the like made by the terminal device 10. The positioning unit 14 may obtain such information to determine the location of the terminal device 10. Alternatively, the location may be determined by an optical sensor, an infrared sensor, or the like provided in the terminal device 10.

[0057] The positioning unit 14 may measure the position of the terminal device 10 using one or a combination of the above-mentioned positioning means, as needed.

[0058] (Sensor unit 20) The sensor unit 20 includes various sensors mounted on or connected to the terminal device 10. The connection may be wired or wireless. For example, the sensors may be detection devices other than the terminal device 10, such as wearable devices or wireless devices. In the example shown in FIG. 2 , the sensor unit 20 includes an acceleration sensor 21, a gyro sensor 22, a barometric pressure sensor 23, a temperature sensor 24, a sound sensor 25, a light sensor 26, a magnetic sensor 27, and an image sensor (camera) 28.

[0059] The above-described sensors 21 to 28 are merely examples and are not intended to be limiting. That is, the sensor unit 20 may be configured to include some of the sensors 21 to 28, or may include other sensors such as a humidity sensor in addition to or instead of the sensors 21 to 28.

[0060] The acceleration sensor 21 is, for example, a three-axis acceleration sensor, and detects physical movements of the terminal device 10, such as the direction of movement, speed, and acceleration of the terminal device 10. The gyro sensor 22 detects physical movements of the terminal device 10, such as tilt in three axial directions, based on the angular velocity of the terminal device 10. The air pressure sensor 23 detects, for example, the air pressure around the terminal device 10.

[0061] Since the terminal device 10 includes the acceleration sensor 21, the gyro sensor 22, the atmospheric pressure sensor 23, etc., it is possible to measure the position of the terminal device 10 using a technique such as Pedestrian Dead-Reckoning (PDR) that uses these sensors 21 to 23. This makes it possible to obtain indoor position information that is difficult to obtain using a positioning system such as GPS.

[0062] For example, the number of steps, walking speed, and distance walked can be calculated using a pedometer that uses the acceleration sensor 21. In addition, the direction of travel, line of sight, and body tilt of the user U can be determined using the gyro sensor 22. In addition, the altitude and floor on which the terminal device 10 of the user U is located can be determined from the air pressure detected by the air pressure sensor 23.

[0063] The temperature sensor 24 detects, for example, the temperature around the terminal device 10. The sound sensor 25 detects, for example, the sound around the terminal device 10. The light sensor 26 detects the illuminance around the terminal device 10. The magnetic sensor 27 detects, for example, the geomagnetism around the terminal device 10. The image sensor 28 captures an image around the terminal device 10.

[0064] The above-mentioned air pressure sensor 23, temperature sensor 24, sound sensor 25, light sensor 26, and image sensor 28 can detect the air pressure, temperature, sound, and illuminance, respectively, and capture images of the surroundings, thereby detecting the environment and situation around the terminal device 10. Furthermore, the accuracy of the location information of the terminal device 10 can be improved based on the environment and situation around the terminal device 10.

[0065] (control unit 30) The control unit 30 includes, for example, a microcomputer having a CPU (Central Processing Unit) or MPU (Micro Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), input / output ports, etc., and various other circuits. The control unit 30 may also be configured with hardware such as an integrated circuit, for example, an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 30 includes a transmitting unit 31, a receiving unit 32, and a processing unit 33.

[0066] (Transmitter 31) The transmission unit 31 can transmit, for example, various information input by the user U using the input unit 13, various information detected by each sensor 21 to 28 mounted on or connected to the terminal device 10, and location information of the terminal device 10 measured by the positioning unit 14 to the server device 100 via the communication unit 11.

[0067] (Receiving unit 32) The receiving unit 32 can receive various types of information provided by the server device 100 and requests for various types of information from the server device 100 via the communication unit 11.

[0068] (Processing unit 33) The processing unit 33 controls the entire terminal device 10, including the display unit 12. For example, the processing unit 33 can output various information transmitted by the transmitting unit 31 and various information received from the server device 100 by the receiving unit 32 to the display unit 12 for display.

[0069] (Storage unit 40) The storage unit 40 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), an optical disk, etc. The storage unit 40 stores various programs, various data, etc.

[0070] [4. Server device configuration example] Next, the configuration of the server device 100 according to the embodiment will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the configuration of the server device 100 according to the embodiment. As shown in Fig. 3, the server device 100 includes a communication unit 110, a storage unit 120, and a control unit 130.

[0071] (Communication unit 110) The communication unit 110 is realized by, for example, a network interface card (NIC), etc. The communication unit 110 is connected to a network N by wire or wirelessly.

[0072] (Storage unit 120) The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as an HDD, an SSD, an optical disk, etc. The storage unit 120 may store attribute information and history information (log data) of the user U together with identification information (such as a user ID) indicating the user U.

[0073] (control unit 130) The control unit 130 is a controller, and is realized by, for example, a central processing unit (CPU), a micro processing unit (MPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or the like, by executing various programs (corresponding to an example of an information processing program) stored in a storage device inside the server device 100 using a storage area such as a RAM as a working area. In the example shown in FIG. 3 , the control unit 130 has an acquisition unit 131, an estimation unit 132, an extraction unit 133, a summarization unit 134, a classification unit 135, a comparison unit 136, and a presentation unit 137.

[0074] (Acquisition part 131) The acquisition unit 131 acquires a search query input by a user U. For example, when the user U inputs a search query into a search engine or the like to perform a keyword search, the acquisition unit 131 acquires the search query via the communication unit 110. That is, the acquisition unit 131 acquires, via the communication unit 110, the keywords input by the user U into the search box of a search engine, website, or app.

[0075] Furthermore, the acquisition unit 131 acquires user information about the user U via the communication unit 110. For example, the acquisition unit 131 acquires identification information (such as a user ID) indicating the user U, location information of the user U, attribute information of the user U, etc. from the terminal device 10 of the user U. Furthermore, the acquisition unit 131 may acquire the identification information indicating the user U, attribute information of the user U, etc. when the user U is registered. Then, the acquisition unit 131 stores the user information in the storage unit 120.

[0076] Furthermore, the acquisition unit 131 acquires various types of history information (log data) indicating the behavior of the user U via the communication unit 110. For example, the acquisition unit 131 acquires various types of history information indicating the behavior of the user U from the terminal device 10 of the user U or from various servers based on the user ID or the like. Then, the acquisition unit 131 stores the various types of history information in the storage unit 120.

[0077] (Estimation part 132) The estimation unit 132 estimates a major event that is currently a hot topic in society based on either (at least one of) the group of information posted on the first medium or the group of information posted on the second medium. Alternatively, the estimation unit 132 estimates a common event that is currently a hot topic in the group of information posted on the first medium and the group of information posted on the second medium.

[0078] (Extraction part 133) The extraction unit 133 extracts a group of information posted on a predetermined event from each of a group of information posted on a first medium and a group of information posted on a second medium. For example, the extraction unit 133 extracts a group of information related to the predetermined event from the group of information posted on each medium. The extraction unit 133 may be included in the acquisition unit 131 described above. That is, the extraction unit 133 may be one of the functions of the acquisition unit 131 described above. In this case, the acquisition unit 131 may acquire a group of information posted on a first medium and a group of information posted on a second medium related to the predetermined event.

[0079] For example, the extraction unit 133 extracts a group of information posted about an estimated major event from each of the group of information posted on the first medium and the group of information posted on the second medium. Alternatively, the extraction unit 133 extracts a group of information posted about an estimated common event from each of the group of information posted on the first medium and the group of information posted on the second medium.

[0080] From another perspective, the extraction unit 133 extracts a group of information posted on a predetermined event from each of the group of information posted in the first domain and the group of information posted in the second domain.

[0081] (Summary 134) The summarizing unit 134 summarizes the main points of each of the information group posted on the first medium and the information group posted on the second medium regarding a predetermined event.

[0082] (Classification Department 135) The classification unit 135 classifies each of the information group posted on the first medium and the information group posted on the second medium regarding a predetermined event by item. For example, the classification unit 135 classifies each of the main points of the information group posted on the first medium and the main points of the information group posted on the second medium regarding a predetermined event by item.

[0083] The classification unit 135 classifies each of the information group posted on the first medium and the information group posted on the second medium into predetermined categories. Alternatively, the classification unit 135 classifies each of the information group posted on the first medium and the information group posted on the second medium into categories of common or similar content, and automatically sets categories based on the classified content.

[0084] (Comparison unit 136) The comparison unit 136 compares the direction of opinions of the information groups posted on the first medium and the second medium regarding a predetermined event. At this time, the comparison unit 136 compares the main points of the information group posted on the first medium with the main points of the information group posted on the second medium to compare the direction of opinions. Furthermore, the comparison unit 136 compares the direction of opinions of the information groups posted on the first medium and the second medium for each item. For example, the comparison unit 136 compares the main points of the information group posted on the first medium with the main points of the information group posted on the second medium for each item to compare the direction of opinions.

[0085] Furthermore, when there is a discrepancy between the directions of opinions in the information groups posted on the first medium and the second medium, the comparison unit 136 classifies the directions of each opinion as either positive, negative, or neutral. For example, the comparison unit 136 compares, for each item, the main points of the information group posted on the first medium with the main points of the information group posted on the second medium, and when there is a discrepancy between the directions of opinions, classifies the directions of each opinion as either positive, negative, or neutral.

[0086] From another perspective, the comparison unit 136 compares the directionality of opinions of information posted in the first domain and the second domain regarding a predetermined event.

[0087] (Presentation part 137) The presentation unit 137 presents content that visualizes the divergence in the direction of opinions of a group of information posted on a first medium and a second medium. For example, the presentation unit 137 presents content that visualizes the divergence in the direction of opinions of a group of information posted on a first medium and a second medium for each item. At this time, the presentation unit 137 provides and displays the content that visualizes the divergence in the direction of opinions of a group of information posted on a first medium and a second medium for each item to the terminal device 10 of the user U via the communication unit 110. Note that the presentation unit 137 may be a display control unit that controls the screen display of the terminal device 10 of the user U using an API or the like.

[0088] Furthermore, the presenting unit 137 presents content that visualizes the directionality of opinions of the information group posted on the first medium and the second medium, for each of positive, negative, and neutral.

[0089] From another perspective, the presenting unit 137 presents content that visualizes the divergence in the direction of opinions of the information groups posted in the first domain and the second domain.

[0090] The above content may be generated by the presenting unit 137 or the comparing unit 136.

[0091] [5. Processing Procedure] Next, a processing procedure by the server device 100 according to the embodiment will be described with reference to Fig. 4. Fig. 4 is a flowchart showing the processing procedure according to the embodiment. Note that the processing procedure shown below is repeatedly executed by the control unit 130 of the server device 100.

[0092] For example, as shown in FIG. 4, the estimation unit 132 of the server device 100 estimates major events that are currently trending in society or common events that are currently trending in society based on either or both of a group of information posted on a first medium and a group of information posted on a second medium (step S101).

[0093] Next, the extraction unit 133 of the server device 100 extracts information groups posted regarding the estimated event from each of the information groups posted on the first medium and the information groups posted on the second medium (step S102).

[0094] Next, the summarizing unit 134 of the server device 100 aggregates and summarizes the information groups posted on the first medium and the information groups posted on the second medium regarding the event, and summarizes the main points for each group of information posted on each medium (step S103).

[0095] Next, the classification unit 135 of the server device 100 classifies the main points of the information group posted on the first medium and the main points of the information group posted on the second medium regarding the event by item (step S104).

[0096] Next, the comparison unit 136 of the server device 100 compares, for each item, the gist of the information group posted on the first medium with the gist of the information group posted on the second medium (step S105).

[0097] At this time, the comparison unit 136 of the server device 100 determines whether or not there is a divergence in the direction of the opinions (step S106). If there is no divergence in the direction of the opinions (step S106; No), the comparison unit 136 ends the process without taking any action. Alternatively, other key points are investigated.

[0098] Furthermore, if there is a discrepancy in the direction of the opinions (step S106; Yes), the comparison unit 136 of the server device 100 classifies the direction of each opinion into positive, negative, or neutral (step S107).

[0099] Next, the presentation unit 137 of the server device 100 presents content that visualizes the divergence in the direction of opinions of the information group posted on the first medium and the second medium for each item, either positive, negative, or neutral (step S108).

[0100] [6. Modifications] The terminal device 10 and the server device 100 described above may be implemented in various different forms other than the above embodiment. Therefore, modifications of the embodiment will be described below.

[0101] In the above embodiment, some or all of the processing executed by the server device 100 may actually be executed by the terminal device 10 (or an application running on the terminal device 10). For example, the processing may be completed in a stand-alone manner (by the terminal device 10 alone). In this case, the terminal device 10 is assumed to have the functions of the server device 100 in the above embodiment. Furthermore, in the above embodiment, the terminal device 10 cooperates with the server device 100, and therefore, from the perspective of the user U, it appears that the processing of the server device 100 is also being executed by the terminal device 10. In other words, from another perspective, the terminal device 10 can also be said to be equipped with the server device 100.

[0102] In the above embodiment, the server device 100 compares SNS posts related to a predetermined event with comments on news articles. However, in practice, the server device 100 may compare SNS posts from a first domain with SNS posts from a second domain, or may compare comments on articles on a news site from a first domain with comments on articles on a news site from a second domain. That is, the server device 100 may compare posts from different SNSs, or may compare comments on different news sites. That is, the first domain and the second domain may be domains of the same type of media, or may be domains of different types of media.

[0103] In the above embodiment, the server device 100 compares SNS posts about a predetermined event with comments on news articles, but in reality, the comparison is not limited to text information, and the content of posted images, audio, videos, etc. For example, the comparison may be audio data or video data in videos or broadcasts.

[0104] Furthermore, in the above embodiment, the server device 100 compares the SNS posts with the comments on the news article, but in reality, the comments may be posted on an e-commerce site, a video site, a Q&A site, a specialized field site, a life advice site, etc. For example, regarding a certain product, the comments posted on the e-commerce site may be compared with the comments on the news article, or the SNS posts may be compared with the comments posted on the e-commerce site.

[0105] [7. Effects] As described above, the information processing device (terminal device 10 and server device 100) according to the present application is characterized by comprising an extraction unit 133 that extracts a group of information posted on a predetermined event from each of a group of information posted on a first medium and a group of information posted on a second medium; a comparison unit 136 that compares the direction of opinions of the group of information posted on the first medium and the second medium regarding the predetermined event; and a presentation unit 137 that presents content that visualizes the divergence in the direction of opinions of the group of information posted on the first medium and the second medium.

[0106] This makes it possible to visualize the difference in opinions on the same issue due to differences in media.

[0107] The information processing device according to the present application further includes a summarizing unit 134 that summarizes the main points of each of the information group posted on the first medium and the information group posted on the second medium regarding a predetermined event. The comparing unit 136 compares the main points of the information group posted on the first medium with the main points of the information group posted on the second medium to compare the direction of opinions.

[0108] This allows us to summarize the main points of information from each medium and compare the direction of opinions.

[0109] The information processing device according to the present application further includes a classification unit 135 that classifies, by item, a group of information posted on a first medium and a group of information posted on a second medium regarding a predetermined event. A comparison unit 136 compares, for each item, the direction of opinions in the group of information posted on the first medium and the group of information posted on the second medium. A presentation unit 137 presents content that visualizes, for each item, the difference in the direction of opinions in the group of information posted on the first medium and the group of information posted on the second medium.

[0110] This allows us to categorize information groups by item for each medium and compare the direction of opinions for each item.

[0111] The classification unit 135 classifies each of the information group posted on the first medium and the information group posted on the second medium into predetermined categories.

[0112] This allows the information group to be classified into predetermined categories for each medium.

[0113] The classification unit 135 classifies each of the information group posted on the first medium and the information group posted on the second medium into common or similar content, and automatically sets items based on the classified content.

[0114] This allows information groups for each medium to be classified by common or similar content, and items to be automatically set.

[0115] The information processing device according to the present application further includes an estimation unit 132 that estimates a major event that is currently a hot topic in society based on either a group of information posted on a first medium or a group of information posted on a second medium. The extraction unit 133 extracts a group of information posted related to the estimated major event from each of the group of information posted on the first medium and the group of information posted on the second medium.

[0116] This makes it possible to estimate major events that are currently the subject of public attention and extract information about the events for each medium.

[0117] Alternatively, the information processing device according to the present application further includes an estimation unit 132 that estimates a common event that is a topic of each of a group of information posted on a first medium and a group of information posted on a second medium. The extraction unit 133 extracts a group of information posted related to the estimated common event for each of the group of information posted on the first medium and the group of information posted on the second medium.

[0118] This makes it possible to extract information groups related to common events for each medium.

[0119] When there is a discrepancy between the direction of opinions of the information group posted on the first medium and the second medium, the comparison unit 136 classifies the direction of each opinion as positive, negative, or neutral. The presentation unit 137 presents content that visualizes the direction of opinions of the information group posted on the first medium and the second medium, respectively, for positive, negative, and neutral.

[0120] This makes it possible to visualize whether the direction of opinions in the information group for each medium is positive, negative, or neutral.

[0121] The extraction unit 133 extracts information posted on a predetermined event from each of the information posted on the first domain and the information posted on the second domain. The comparison unit 136 compares the direction of opinions of the information posted on the first domain and the information posted on the second domain regarding the predetermined event. The presentation unit 137 presents content that visualizes the difference in the direction of opinions of the information posted on the first domain and the information posted on the second domain.

[0122] This makes it possible to visualize the difference in opinions between the information groups posted in the first domain and the second domain regarding a specific event.

[0123] By using any one or a combination of the above-described processes, the information processing device according to the present application can visualize the difference in opinions about the same event due to differences in media.

[0124] [8. Hardware Configuration] The terminal device 10 and the server device 100 according to the above-described embodiments are realized by a computer 1000 having a configuration as shown in Fig. 5, for example. The following description will be given taking the server device 100 as an example. Fig. 5 is a diagram showing an example of a hardware configuration. The computer 1000 is connected to an output device 1010 and an input device 1020, and has a configuration in which a calculation device 1030, a primary storage device 1040, a secondary storage device 1050, an output I / F (Interface) 1060, an input I / F 1070, and a network I / F 1080 are connected via a bus 1090.

[0125] The arithmetic device 1030 operates based on programs stored in the primary storage device 1040 and the secondary storage device 1050, programs read from the input device 1020, and the like, and executes various processes. The arithmetic device 1030 is realized by, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or the like.

[0126] The primary storage device 1040 is a memory device such as a RAM (Random Access Memory) that temporarily stores data used by the arithmetic device 1030 for various calculations. The secondary storage device 1050 is a storage device in which data used by the arithmetic device 1030 for various calculations and various databases are registered, and is realized by a ROM (Read Only Memory), an HDD (Hard Disk Drive), an SSD (Solid State Drive), a flash memory, or the like. The secondary storage device 1050 may be an internal storage device or an external storage device. The secondary storage device 1050 may also be a removable storage medium such as a USB (Universal Serial Bus) memory or an SD (Secure Digital) memory card. The secondary storage device 1050 may also be cloud storage (online storage), a NAS (Network Attached Storage), a file server, or the like.

[0127] The output I / F 1060 is an interface for transmitting information to be output to an output device 1010 that outputs various types of information, such as a display, a projector, a printer, etc., and is realized by a connector conforming to a standard such as USB (Universal Serial Bus), DVI (Digital Visual Interface), or HDMI (High Definition Multimedia Interface), etc. The input I / F 1070 is an interface for receiving information from various input devices 1020, such as a mouse, a keyboard, a keypad, a button, a scanner, etc., and is realized by a USB, etc.

[0128] Furthermore, the output I / F 1060 and the input I / F 1070 may be wirelessly connected to the output device 1010 and the input device 1020, respectively. That is, the output device 1010 and the input device 1020 may be wireless devices.

[0129] The output device 1010 and the input device 1020 may be integrated into one device, such as a touch panel. In this case, the output I / F 1060 and the input I / F 1070 may also be integrated into one device as an input / output I / F.

[0130] The input device 1020 may be a device that reads information from, for example, an optical recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0131] The network I / F 1080 receives data from other devices via the network N and sends it to the arithmetic device 1030, and also transmits data generated by the arithmetic device 1030 to other devices via the network N.

[0132] The arithmetic unit 1030 controls the output device 1010 and the input device 1020 via the output I / F 1060 and the input I / F 1070. For example, the arithmetic unit 1030 loads a program from the input device 1020 or the secondary storage device 1050 onto the primary storage device 1040 and executes the loaded program.

[0133] For example, when the computer 1000 functions as the server device 100, the arithmetic unit 1030 of the computer 1000 executes a program loaded onto the primary storage device 1040 to realize the functions of the control unit 130. The arithmetic unit 1030 of the computer 1000 may also load a program acquired from another device via the network I / F 1080 onto the primary storage device 1040 and execute the loaded program. The arithmetic unit 1030 of the computer 1000 may also cooperate with the other device via the network I / F 1080 to call and use the functions and data of a program from another program of the other device.

[0134] [9. Other] Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. Furthermore, the above-described components include those that can be easily imagined by a person skilled in the art, those that are substantially the same, and those that are within the scope of so-called equivalents. Furthermore, the above-described components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the components can be made without departing from the spirit of the above-described embodiments.

[0135] Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using a known method. In addition, the information including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

[0136] Furthermore, the components of each device shown in the figure are conceptual functional components and do not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

[0137] For example, the above-mentioned server device 100 may be realized by multiple server computers, and depending on the function, the configuration can be flexibly changed, such as by calling an external platform using an API (Application Programming Interface) or network computing.

[0138] Furthermore, the above-described embodiments and modifications can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0139] Furthermore, the above-mentioned "section, module, unit" can be read as "means" or "circuit," etc. For example, an acquisition unit can be read as an acquisition means or an acquisition circuit. [Explanation of symbols]

[0140] 1. Information Processing Systems 10 Terminal Equipment 100 Server device 110 Communications Department 120 Storage section 130 Control Unit 131 Acquisition Department 132 Estimation Department 133 Extraction part 134 Summary 135 Classification Department 136 Comparison Section 137 Presentation section

Claims

1. an extraction unit that extracts a group of information posted on a predetermined event from each of the group of information posted on the first medium and the group of information posted on the second medium; a comparison unit that compares the direction of opinions of information posted on the first medium and the second medium regarding the predetermined event; a presentation unit that presents content that visualizes a divergence in the direction of opinions of information groups posted on the first medium and the second medium; An information processing device comprising:

2. a summarizing unit that summarizes the main points of each of the information group posted on the first medium and the information group posted on the second medium regarding the predetermined event; The comparison unit compares the main points of the information group posted on the first medium with the main points of the information group posted on the second medium, and compares the direction of opinions.

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

3. a classification unit that classifies the information group posted on the first medium and the information group posted on the second medium regarding the predetermined event by item, The comparison unit compares the direction of opinions of the information groups posted on the first medium and the second medium for each item, The presentation unit presents content that visualizes, for each item, a divergence in the direction of opinions of information groups posted on the first medium and the second medium.

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

4. The classification unit classifies each of the information group posted on the first medium and the information group posted on the second medium into predetermined categories.

4. The information processing apparatus according to claim 3,

5. The classification unit classifies the information group posted on the first medium and the information group posted on the second medium into groups of common or similar content, and automatically sets items based on the classified content.

4. The information processing apparatus according to claim 3,

6. The information processing device further includes an estimation unit that estimates a major event that is currently a hot topic in society based on either the information group posted on the first medium or the information group posted on the second medium; The extraction unit extracts a group of information posted on the first medium and a group of information posted on the second medium, the group of information being posted relating to the estimated major event.

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

7. The information sharing system further includes an estimation unit that estimates a common phenomenon that is a topic of each of the information group posted on the first medium and the information group posted on the second medium, The extraction unit extracts a group of information posted on the first medium and a group of information posted on the second medium, the group of information being related to the estimated common event.

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

8. When there is a discrepancy between the direction of opinions of the information group posted on the first medium and the second medium, the comparison unit classifies the direction of each opinion into either positive, negative, or neutral; The presentation unit presents content that visualizes the direction of opinions of the information group posted on the first medium and the second medium, for each of positive, negative, and neutral opinions.

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

9. The extraction unit extracts a group of information posted on a predetermined event from each of a group of information posted on a first domain and a group of information posted on a second domain; The comparison unit compares the direction of opinions of the information groups posted in the first domain and the second domain regarding the predetermined event, The presentation unit presents content that visualizes a divergence in the direction of opinions of information groups posted on the first domain and the second domain.

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

10. An information processing method executed by an information processing device, an extraction step of extracting a group of information posted on a predetermined event from each of the group of information posted on the first medium and the group of information posted on the second medium; a comparison step of comparing the direction of opinions of the information groups posted on the first medium and the second medium regarding the predetermined event; a presentation step of presenting content that visualizes the divergence in the direction of opinions of information groups posted on the first medium and the second medium; An information processing method comprising:

11. an extraction step of extracting a group of information posted on a predetermined event from each of the group of information posted on the first medium and the group of information posted on the second medium; a comparison step of comparing the direction of opinions of the information groups posted on the first medium and the second medium regarding the predetermined event; a presentation step of presenting content that visualizes the divergence in the direction of opinions of information groups posted on the first medium and the second medium; An information processing program characterized by causing a computer to execute the above.

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