Information providing system

Abstract

To provide an information providing system configured to provide a user with information on post emotion at a spot, for each spot, in a mode so as to identify the type of more concrete emotion.SOLUTION: An information providing system is configured to: acquire a posted sentence posted on a network together with spot information specifying a spot associated with the posted sentence; analyze the acquired posted sentence to predict post emotion which is the emotion of a poster who has posted the posted sentence; aggregate the predicted post emotion for each spot associated with the posted sentence to be the source of analysis, and specify post emotion for each spot; display, on a screen, post emotion at a designated spot; specify to which of basic emotions in which the post emotion is divided into a plurality of types in the specification of the post emotion the specified post emotion belongs, and also specify to which of application emotions generated by the combination of the different types of basic emotions the specified post emotion belongs when a predetermined condition is satisfied; and separately display the basic emotion and the application emotion specified, as that the post emotion belongs to.SELECTED DRAWING: Figure 13

Description

Technical Field

[0001] The present invention relates to an information providing system that provides information based on posted texts posted on a network.

Background Art

[0002] In recent years, systems have been provided that allow users to post posted texts on a computer network via a terminal and view posted texts posted by other users. For example, there are blogs, SNS (Social Network Service), X (registered trademark), chats, etc. (hereinafter referred to as SNS, etc.). In addition, many of these posted texts include posted texts in which the poster has posted information about a location such as a facility visited.

[0003] Here, the above SNS, etc. have the merit of being able to quickly obtain the latest information experienced or felt by users who have actually visited the site, and various systems for providing information based on posted texts posted on the SNS, etc. have been proposed. For example, Japanese Patent Application Laid-Open No. 2019-20784 discloses a technique of collecting posted texts posted on an SNS and information for specifying the posting position, analyzing the posted texts posted at the same location, and determining whether positive feelings or negative feelings are dominant among the posters who have posted the posted texts for that location as a whole, and displaying the determination result as an emotion mark on a map image.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Here, in Patent Document 1 mentioned above, by collecting and analyzing posted texts on SNS etc. for each location, it determines whether the sentiment of the posters at that location is positive or negative as a whole and provides information to the user. However, even if it is generally said to be positive sentiment or negative sentiment, there is a problem that the sentiment lacks specificity and the user cannot grasp what specific sentiment it is.

[0006] The present invention has been made to solve the above-mentioned conventional problems, and by analyzing posted texts on the network, it is possible to provide information to the user in a manner that specifies information regarding the posted sentiment at each location to even more specific types of sentiment. The purpose is to provide an information providing system.

Means for Solving the Problem

[0007] To achieve the above object, the information providing system according to the present invention includes a posted text information acquisition means for acquiring a posted text posted on the network together with location information specifying the location associated with the posted text, a sentiment prediction means for predicting a posted sentiment, which is the sentiment of the poster who posted the posted text, by analyzing the posted text acquired by the posted text information acquisition means, a location sentiment specifying means for classifying and aggregating the posted sentiment predicted by the sentiment prediction means for each location associated with the posted text serving as the analysis source, and specifying the posted sentiment for each location, and a posted sentiment display means for displaying the posted sentiment at a designated location on the screen. The location sentiment specifying means specifies not only to which of the basic sentiments into which the posted sentiment is classified into a plurality of types it belongs, but also, when a predetermined condition is satisfied, to which of the applied sentiments generated by a combination of different types of the basic sentiments it belongs. The posted sentiment display means displays the basic sentiment and the applied sentiment to which the posted sentiment is specified to belong. Incidentally, the "basic sentiment" is, for example, eight sentiments of joy, disgust, anger, fear, sadness, expectation, surprise, and trust. However, it is not limited to the above classification, and it may be six sentiments of anger, disgust, horror, happiness, sadness, and surprise, for example.

Effect of the Invention

[0008] According to the information providing system of the present invention having the above configuration, by analyzing the posted text posted on the network, it is possible to provide the user with information regarding the posted sentiment at each location in a manner that specifies the information regarding the posted sentiment at that location even to more specific types of sentiment. As a result, the user can obtain a more accurate evaluation based on the posted text for the location.

Brief Description of the Drawings

[0009]

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Best Mode for Carrying Out the Invention

[0010] Hereinafter, the information providing system according to the present invention will be described in detail with reference to the drawings based on a specific embodiment. First, the schematic configuration of the information providing system 1 according to the present embodiment will be described with reference to FIG. 1. FIG. 1 is a schematic configuration diagram showing the information providing system 1 according to the present embodiment.

[0011] As shown in FIG. 1, the information providing system 1 according to the present embodiment basically includes an information providing server 3 provided in the information providing center 2 and a communication terminal 5 possessed by the user 4. Further, the information providing server 3 and the communication terminal 5 are configured to be able to transmit and receive electronic data to and from each other via the communication network 6. Note that examples of the communication terminal 5 include a mobile phone, a smartphone, a tablet terminal, a personal computer, and a navigation device which is an in-vehicle device.

[0012] Here, the information providing server 3 is a server device that manages information to be provided to the communication terminal 5 (that is, the user who possesses the communication terminal 5). The information providing server 3 stores information on information providing locations across the country to be provided to the communication terminal 5 in the distribution information DB 7. Note that the information providing locations are not particularly limited in genre or scale, and examples include commercial facilities such as restaurants and retail stores, public facilities such as stations and hospitals, and other accommodation facilities, parking lots, etc. Also, it is not limited to facilities, and for example, tourist spots may be used. Further, as information on the information providing locations stored in the distribution information DB 7 as described later, in addition to the name, address, position coordinates, telephone number, business hours, etc. of the information providing locations, in this embodiment, information on "posted sentiment" identified by analyzing posted texts on the network is particularly included. Details regarding the posted sentiment will be described later. Then, the information providing server 3 provides (distributes) information on the information providing locations stored in the DB to the communication terminal 5 via the communication network 6.

[0013] In addition, the communication terminal 5 is an information terminal possessed by the user and equipped with communication functions, navigation functions, etc. For example, it corresponds to a mobile phone, a smartphone, a tablet terminal, a personal computer, a navigation device that is an in-vehicle device, etc. In particular, when the communication terminal 5 is a terminal capable of executing applications such as a smartphone, as one of the applications, it displays a map image of an area designated by the user, and can display an icon indicating the posted emotion with respect to the position of the information-providing point included in the displayed map image. An application program is installed. Further, in the above application program, by selecting an icon displayed on the map image, more detailed information regarding the information-providing point corresponding to the selected icon can be obtained from the information-providing server 3 and guided. Note that the selection of the information-providing point to be guided can be made using the above map image, or can also be made from the search results obtained by inputting search conditions. Also, the function of guiding regarding these information-providing points may be a part of the navigation function for guiding the movement to the destination, or may be executed by an application program different from the navigation function.

[0014] In addition, the communication network 6 includes a large number of base stations arranged throughout the country and a communication company that manages and controls each base station, and is configured by connecting the base stations and the communication company to each other by wire (optical fiber, ISDN, etc.) or wirelessly. Here, the base station has a transceiver (transmitter / receiver) and an antenna for communicating with the communication terminal 5. Then, while the base station performs wireless communication between communication companies, it becomes the end of the communication network 6 and has the role of relaying the communication of the communication terminal 5 within the range (cell) where the radio wave of the base station reaches with the information-providing server 3.

[0015] On the one hand, the information providing server 3 included in the above information providing system 1 can obtain a posted text on the network from an SNS server 8 that provides a social networking service (hereinafter referred to as SNS) existing on the network, together with location information for identifying the location associated with the posted text and time information for identifying the posted time (collectively referred to as posted text information). Note that the method of obtaining the posted text information may be through the network or through a storage medium such as a flash memory.

[0016] Here, the SNS server 8 is a server device that constructs an SNS on the network. An SNS is a community-type service for constructing connections with others (which may be not only individuals but also corporations). Service users access from clients such as smartphones, tablet terminals, and personal computers, and by posting messages, images, etc., the content can be viewed by other service users. In addition, other service users who have viewed the message or image can comment on the post, quote and retweet (repost) the content, follow the poster through the follow function, or give a positive reaction (e.g., 'Good', 'Like') when they empathize with the posted content. Note that in this embodiment, it is an open-type SNS that can be used by anyone as long as they are registered users without any particular restrictions on the users to be used. Also, the SNS server 8 is provided with a storage DB 9, and messages, image data, the date and time of posting, hashtag, the location of posting (which may be a facility name or a position coordinate), the number of positive reactions and the number of retweets received from other service users for each post, the number of followers for each service user, etc. posted by service users are stored in the storage DB 9.

[0017] Then, in the present embodiment, the information providing server 3 acquires, as post information, from the SNS server 8, among the data stored in the storage DB 9, in particular, the combination of the content of the post (which may be only the message or may include an image if an image is attached), the date and time when the post was made, and the location where the post was made.

[0018] Next, the configuration of the information providing server 3 in the information providing system 1 will be described in more detail with reference to FIG. 2. As shown in FIG. 2, the information providing server 3 includes a server control unit 11, a post information DB 13 as information recording means connected to the server control unit 11, a distribution information DB 7, a map information DB 14, and a server-side communication device 15.

[0019] The server control unit 11 is a control unit (such as an MCU or an MPU) that controls the entire information providing server 3, and includes a CPU 21 as an arithmetic unit and a control unit, a RAM 22 used as a working memory when the CPU 21 performs various arithmetic processes, a ROM 23 in which a control program and, in addition, an emotion analysis processing program (FIG. 6) and an information providing processing program (FIG. 11) described later are recorded, and an internal storage device such as a flash memory 24 that stores the program read from the ROM 23. Note that the server control unit 11 has various means as processing algorithms. For example, the post information acquisition means acquires a post posted on the network together with location information for specifying the location associated with the post. The emotion prediction means predicts the post emotion, which is the emotion of the poster who posted the post, by analyzing the post acquired by the post information acquisition means. The location emotion specifying means classifies and aggregates the post emotions predicted by the emotion prediction means for each location associated with the post serving as the analysis source, and specifies the post emotion for each location.

[0020] In addition, the posted text information DB 13 is a storage means for storing the posted text information acquired from the SNS server 8. Here, the posted text information includes the posted text posted on the network as described above, the location information for specifying the location linked to the posted text, and the time information for specifying the posted time. Note that, in the present embodiment, the "location linked to the posted text" is the place where the posted text was posted (the location where the poster who posted the posted text is located). However, for example, when the posted text includes a place name, or when the place name is linked as a hashtag, the place name may be regarded as the location linked to the posted text.

[0021] Here, FIG. 3 is a diagram showing an example of the posted text information stored in the posted text information DB 13. As shown in FIG. 3, in the posted text information DB 13, the content of the posted text (text data of the message) is stored in association with the location name indicating the location linked to the posted text and the date and time of posting. Note that, in the example shown in FIG. 3, it is stored separately for each location name linked to the posted text, but how to classify and store it can be changed as appropriate. Also, in the example shown in FIG. 3, the content of the posted text is only text information, but when an image is attached, the image may also be included. Further, although the location name is stored as the information indicating the location linked to the posted text, it may be the position coordinates instead of the location name. Note that when the SNS server 8 receives the posted text posted on the network by the service user (poster), the position coordinates of the terminal used by the service user for posting (specified by GPS or the like provided in the terminal) are also acquired as the place where the posted text was posted. Therefore, when storing the specific location name where the posted text was posted as the posted text information as shown in FIG. 3, it is necessary to refer to the map information and specify the location name of the location where the service user is predicted to be located from the acquired position coordinates. However, the processing may be performed by the SNS server 8 or the information providing server 3. Also, for the posted date and time, only the time may be stored, or on the other hand, the day of the week and the like may also be included.

[0022] Also, the distribution information DB7 is a storage means that stores various types of information regarding information-providing locations targeted for information provision across the country as described above. Here, FIG. 4 is a diagram showing an example of the information stored in the distribution information DB7.

[0023] As shown in FIG. 4, in the distribution information DB7, for information-providing locations across the country, location ID, location name, location position coordinates, detailed information about the location, current congestion status, posted sentiment, etc. are stored. However, it is not necessarily required to store all of these pieces of information in the distribution information DB7. Incidentally, regarding "posted sentiment", specifically, it is what identifies which sentiment the sentiment of the poster (accurately, the poster who posted the posted text at that location) regarding the posted text about that location is as a whole, and is identified by the server control unit 11 by analyzing the posted text information stored in the posted text information DB13 as described later. Incidentally, there are various human emotions, but in particular, in this embodiment, the posted sentiment is identified by the basic emotions (primary emotions) roughly classified into 8 types and the applied emotions (secondary emotions) generated by combinations of different types of basic emotions. However, regarding the applied emotions, they are identified only when a predetermined condition is satisfied, that is, when it is difficult to convey the posted sentiment to the user only with the basic emotions. Otherwise, that is, when the posted sentiment can be conveyed to the user only with the basic emotions, the posted sentiment is identified only by the basic emotions. Furthermore, as shown in FIG. 4, the distribution information DB7 also stores bar graphs comparing the magnitudes of emotions for each of the 8 types of basic emotions, line graphs showing the transition of emotions over time, etc.

[0024] For example, in the distribution information DB7 shown in FIG. 4, information such as facility information, current congestion status, and posted sentiment is stored for "XX Station" at the position coordinates (x1, y1). Similarly, information regarding other information-providing locations is also stored. Note that the bar graph showing the sentiment in FIG. 4 compares the magnitudes (sentiment values) of the eight basic sentiments, and is a tabulation of the sentiment analysis results of the posted texts posted at that information-providing location. For example, as a result of analyzing the posted text, a process of determining and counting which of joy, disgust, anger, fear, sadness, expectation, surprise, and trust the posted sentiment of the posted text belongs to is performed for all the posted texts posted at that information-providing location. That is, it shows that the sentiment with a high value in the bar graph is the main strong posted sentiment at that information-providing location. On the other hand, the line graph shows the transition of the sentiment value with respect to time in a rectangular coordinate system with the time axis on the horizontal axis and the sentiment value on the vertical axis, targeting the basic sentiment determined to have a high sentiment value particularly at that information-providing location among the eight basic sentiments. However, the posted sentiment is not limited to such expressions shown by bar graphs or line graphs, and may be shown by a pie chart or a scatter diagram. Or it may be shown by text or a table instead of a graph.

[0025] Also, the map information DB14 is a storage means for storing map information. The map information is composed of various information necessary for route search, route guidance, and map display, including a road network. For example, it consists of link data regarding roads (links), node data regarding node points, intersection data regarding each intersection, location data regarding locations such as facilities, map display data for displaying a map, search data for searching for a route, search data for searching for a location, and the like.

[0026] Then, the server control unit 11 uses the map information DB14 to, in response to a request from the communication terminal 5, transmit map display data for displaying a map image on the communication terminal 5, search for a location corresponding to the input search condition, or perform a route search from the departure point to the destination using the map information stored in the map information DB14 when a route search request is received.

[0027] However, when the communication terminal 5 has map information, the communication terminal 5 can perform the above processing using the map information it has. In that case, the map information DB14 is not necessarily required in the information providing server 3.

[0028] On the other hand, the server-side communication device 15 is a communication device for communicating with the communication terminal 5 that is the target of information transmission and reception via the communication network 6. In addition to the communication terminal 5, it is also possible to receive traffic information composed of various information such as traffic jam information, regulation information, and traffic accident information transmitted from the Internet, a traffic information center, for example, a VICS (registered trademark: Vehicle Information and Communication System) center, etc. Furthermore, in addition to traffic information, by communicating with an external server, it is possible to receive weather information in various regions across the country, event information regarding events held across the country, news in various places, congestion information at locations, etc.

[0029] Next, the schematic configuration of the communication terminal 5 owned by the user will be described with reference to FIG. 5. FIG. 5 is a block diagram schematically showing the control system of the communication terminal 5 according to the present embodiment. Hereinafter, the case where the communication terminal 5 is a smartphone will be described as an example.

[0030] As shown in FIG. 5, the communication terminal 5 is connected to a data bus BUS, a CPU 31, a memory 32 in which user information (user ID, name, etc.) regarding the user who owns the communication terminal 5 and application programs are stored, an input / output unit 35 which is an interface such as a microphone 33 and a speaker 34, a display 36 composed of a liquid crystal display panel, etc., an input operation unit 37 composed of a touch panel, a keyboard, etc., a GPS 38, and a transmission / reception circuit unit (RF) 39 that transmits and receives signals to and from the base station of the communication network 6.

[0031] Here, the CPU 31 built into the communication terminal 5 is a control means of the communication terminal 5 that executes various operations according to the operation program stored in the memory 32, and constitutes the communication terminal control unit 41 together with the memory 32. Also, the various processing contents of the communication terminal control unit 41 are displayed on the display 36 as necessary. Note that the communication terminal control unit 41 constitutes various means as a processing algorithm. For example, the post emotion display means displays the specified post emotion for the specified location on the screen.

[0032] In addition, the communication terminal 5 performs communication via the transmission / reception circuit unit 39, and in addition to voice calls, it can also perform Internet communication, receive information on charging facilities from the information providing server 3, and receive traffic information consisting of various information such as traffic jam information, regulation information, and traffic accident information transmitted from a traffic information center, for example, a VICS (registered trademark) center or a probe center.

[0033] In addition, the memory 32 is a storage medium that stores user information (user ID, name, etc.) regarding the user who owns the communication terminal 5, map information, as well as the user's browsing history of the web, the user's movement history which is a history of position information detected based on the GPS 38 and other sensors, schedule information, etc. Also, various application programs including the information providing processing program (Fig. 11) described later are stored. Also, the memory 32 may be constituted by a hard disk, a memory card, etc.

[0034] In addition, the speaker 34 outputs voice guidance for guiding driving along the guiding route (the user's planned movement route) based on an instruction from the communication terminal control unit 41 during the execution of the navigation function, in addition to the voice output of the call.

[0035] In addition, the display 36 is disposed on one surface of the housing, and a liquid crystal display, an organic EL display, or the like is used. Then, a top screen for executing various applications installed in the communication terminal 5, a screen related to the executed application (Internet screen, mail screen, navigation screen, etc.), and various information such as images and videos are displayed. In particular, in this embodiment, a map image of an area designated by the user is displayed, and an icon indicating the posted emotion is displayed at the position of the information providing point included in the displayed map image. Further, when the icon displayed on the map image is selected, more detailed information about the information providing point related to the selected icon is displayed.

[0036] In addition, the input operation unit 37 is composed of a touch panel provided on the front surface of the display 36, a hard button arranged on the housing, or the like. Then, the communication terminal control unit 41 performs control to execute corresponding various operations based on an electrical signal output by pressing the touch panel or the hard button. Note that the input operation unit 37 can also be composed of various keys such as a number / character input key, a cursor key for moving a cursor for selecting the displayed content, and a decision key for confirming the selection.

[0037] In addition, the GPS 38 can detect the current position and current time of the communication terminal 5 (that is, the user) by receiving radio waves generated by artificial satellites. In addition to the GPS 38, the communication terminal 5 may be configured to include another device (for example, a gyro sensor or the like) for detecting the current position and orientation of the communication terminal 5.

[0038] In addition, the transmission / reception circuit unit 39 is a circuit unit for transmitting and receiving signals to and from a base station of the communication network 6 according to a communication standard such as 3G, 4G, or LTE.

[0039] Next, in the information providing system 1 having the above configuration, the sentiment analysis processing program executed by the information providing server 3 will be described with reference to FIG. 6. FIG. 6 is a flowchart of the sentiment analysis processing program according to the present embodiment. Here, the sentiment analysis processing program is executed after a predetermined time (for example, 24 hours) has elapsed since the previous execution, and is a program that identifies "post sentiment" for each information providing location by analyzing the post information stored in the post information DB 13. Note that the programs shown in the flowcharts in FIGS. 6 and 11 below are stored in the RAM 22, ROM 23, etc. provided in the information providing server 3 and are executed by the CPU 21.

[0040] Here, the sentiment analysis processing program executes processing for information providing locations across the country, and "post sentiment" is to be identified for each information providing location. However, it is not necessarily required to execute processing for all information providing locations across the country. For example, it is also possible to execute the processing targeting only specific genres or locations of a predetermined scale or larger. Also, the interval at which the sentiment analysis processing program is executed for each location may be changed.

[0041] First, in step (hereinafter abbreviated as S) 1, the CPU 21 determines whether there is post information associated with the information providing location that is the current evaluation target in the post information DB 13. Note that in order to perform accurate sentiment analysis, it is desirable to exclude old post information from the analysis targets. Basically, it is determined whether there is post information posted within the last three months or within the last six months. Also, it may be determined whether there is at least one or more pieces of post information, but since accurate analysis is difficult with a small number of samples, it may be determined whether there is a predetermined number (for example, 3) or more pieces of post information.

[0042] Here, as shown in FIG. 3, the posted text information DB 13 stores the posted text information obtained in advance from the external SNS server 8. In particular, the content of the posted text (the text data of the message) is stored in association with the location name indicating the location associated with the posted text (the location where the posted text was posted) and the date and time of posting. Therefore, in step S1, it is determined whether there is posted text information associated with the location name of the information providing location to be evaluated.

[0043] And when it is determined that there is posted text information associated with the information providing location to be evaluated this time in the posted text information DB 13 (S1: YES), the process proceeds to S2. On the contrary, when it is determined that there is no posted text information associated with the information providing location to be evaluated this time in the posted text information DB 13 (S1: NO), since no posted text to be analyzed exists for the sentiment of the information providing location to be evaluated, the sentiment analysis processing program is terminated.

[0044] In S2, the CPU 21 extracts and obtains the posted text information associated with the information providing location to be evaluated this time from the posted text information DB 13. Incidentally, in order to perform accurate sentiment analysis, it is desirable to exclude old posted texts from the analysis targets, and basically, the posted text information posted within 3 months or within 6 months is obtained as the target.

[0045] Then, the processes of S3 and S4 below are performed for each of the posted text information obtained in S2, and after executing the processes of S3 and S4 for all the obtained posted text information, the process proceeds to S5.

[0046] First, in S3, the CPU 21 performs sentiment analysis on the posted text information to be processed, and particularly predicts the posting sentiment, which is the sentiment of the poster who posted the text data indicating the posting content, from the text data. Here, there are various methods for sentiment analysis, such as machine learning, rule-based, and combinations thereof. In particular, in this embodiment, sentiment analysis applying machine learning such as deep learning will be used. In sentiment analysis applying machine learning, it is possible to analyze sentiment from text data based on elements such as the meaning of words appearing in a sentence, the context of the words used, and the expression method, rather than analyzing individual words by natural language processing technology.

[0047] Here, in storage media such as the ROM 23 and flash memory 24 of the information providing server 3, a learned learning model 45 used for the above sentiment analysis is recorded. As the learning model 45, for example, a neural network is used. In particular, the learning model 45 of this embodiment is a learning model that has been pre-learned to estimate and output the "ratio of sentiment for each sentiment category (sentiment ratio)" of the posting sentiment from the text data by inputting the text data of the posted text as shown in FIG. 7. Here, in the learning model 45 using a neural network, as shown in FIG. 7, data obtained by multiplying the weight (weight coefficient) by each neuron, which is the output data after performing processing in the input layer on the text data input to the input layer, is input to the next intermediate layer. Then, similarly in the intermediate layer, data obtained by multiplying the weight (weight coefficient) by each neuron, which is the output data after performing processing in the intermediate layer, is input to the next output layer. Then, the sentiment ratio is finally output from the output layer (S4). Incidentally, in the learning of the learning model 45, as the learning progresses, the above weight (weight coefficient) is appropriately changed to a more suitable value and set.

[0048] Also, in this embodiment, it is assumed that the information providing server 3 has a learning model 45 that has been sufficiently trained in advance using teacher data or the like. However, learning of the learning model may also be performed in parallel with the output of the emotion ratio. Also, it is possible to learn without a teacher. Furthermore, the learning model 45 does not necessarily have to consist of only one neural network, and it may include a plurality of neural networks.

[0049] Also, as shown in FIG. 7, the emotion ratio output by the learning model 45 shows the ratio of emotions for each of the eight basic emotions of joy, disgust, anger, fear, sadness, expectation, surprise, and trust for each input text data. The sum of the ratios of each emotion is 1, and the closer it is to 1, the stronger that emotion is expressed in the text data being analyzed. For example, the emotion analysis result for text1 indicates that it is a text in which the two emotions of 'fear' and 'expectation' are strongly expressed respectively. The emotion analysis result for text2 indicates that it is a text in which only the emotion of 'expectation' is strongly expressed. The emotion analysis result for text3 indicates that it is a text with no prominent emotion and little emotion expressed.

[0050] Similarly, for each piece of posted text information obtained in S2, emotion analysis using machine learning is performed (S3). After outputting the emotion ratio for all the obtained posted text information (S4), the process proceeds to S5.

[0051] In S5, the CPU 21 aggregates the emotion ratios output in S4 and calculates an emotion value, which is the total value of the emotion ratios for each of the eight basic emotions that are the basic emotions. The emotion value for each basic emotion calculated in S5 is the result of classifying and aggregating the results of the emotion analysis of the posted text for all the posted texts posted for the information providing location that is the evaluation target this time for each of the basic emotions classified into multiple types, indicating which basic emotion has a high emotion value.

[0052] Next, in S6, the CPU 21 determines the emotional classification of the information-providing location that is the current evaluation target based on the tendency indicated by the emotional value calculated in S5. Here, in the present embodiment, emotional classifications of types 1 to 3 are defined, and in S6, it is determined which of types 1 to 3 the emotional classification of the information-providing location that is the current evaluation target corresponds to.

[0053] Fig. 8 shows examples of each of types 1 to 3 of the emotional classification. 'Type 1' is an emotional classification that shows a tendency for only one emotion to stand out. As a specific condition, the difference in emotional values between the most highly-valued basic emotion and the second-most highly-valued basic emotion is set to be equal to or greater than the first threshold value. The first threshold value is, for example, 40% of the total value obtained by summing up all the emotional values of each emotion. 'Type 2' is an emotional classification that shows a tendency for multiple emotions to stand out. As a specific condition, the difference in emotional values between the most highly-valued basic emotion and the second-most highly-valued basic emotion is less than the first threshold value, and there is at least one basic emotion whose emotional value is equal to or greater than the second threshold value. The first threshold value is, for example, 40% of the total value obtained by summing up all the emotional values of each emotion, and the second threshold value is, for example, 25% of the total value obtained by summing up all the emotional values of each emotion. 'Type 3' is an emotional classification that shows a tendency for there to be no prominent emotion and for the overall emotion to be weak. As a specific condition, there is no basic emotion whose emotional value is equal to or greater than the second threshold value. The second threshold value is, for example, 25% of the total value obtained by summing up all the emotional values of each emotion.

[0054] Thereafter, in S7, the CPU 21 determines whether or not the emotional classification of the information-providing location that is the current evaluation target corresponds to 'Type 1'. If it is determined that the emotional classification of the information-providing location that is the current evaluation target corresponds to 'Type 1' (S7: YES), the process proceeds to S8. On the other hand, if it is determined that the emotional classification of the information-providing location that is the current evaluation target does not correspond to 'Type 1' (S7: NO), the process proceeds to S10.

[0055] Subsequently, in S8, the CPU 21 compares the sentiment values for each basic sentiment calculated in S5 for the information-providing location that is the subject of the current evaluation, and identifies the basic sentiment with the highest sentiment value as the posted sentiment (the basic sentiment to which it belongs) of the information-providing location that is the subject of the current evaluation. For example, in the example of "Type 1" shown in FIG. 8, "disgust" will be identified as the posted sentiment (the basic sentiment to which it belongs).

[0056] Thereafter, in S9, the CPU 21 stores the basic sentiment identified in S8 as the "posted sentiment" for the information-providing location that is the subject of the current evaluation in the distribution information DB 7. Furthermore, a bar graph showing the sentiment values for each basic sentiment calculated in S5 and a line graph showing the transition of the sentiment value over time for the basic sentiment with the highest sentiment value are also generated and stored in the distribution information DB 7 as information regarding the "posted sentiment" for the information-providing location that is the subject of the current evaluation. Note that in order to identify the transition of the sentiment value over time, the posted texts are divided by the posted time (e.g., in one-hour units), and the processes of S3 to S5 are performed for each division, whereby the transition of the sentiment value over time can be identified. As described above, the distribution information DB 7 stores various types of information including information regarding the "posted sentiment" for the information-providing locations that are the subjects of information provision across the country (FIG. 4).

[0057] On the other hand, in S10, the CPU 21 determines whether or not the sentiment classification of the information-providing location that is the subject of the current evaluation corresponds to "Type 2". If it is determined that the sentiment classification of the information-providing location that is the subject of the current evaluation corresponds to "Type 2" (S10: YES), the process proceeds to S11. In contrast, if it is determined that the sentiment classification of the information-providing location that is the subject of the current evaluation does not correspond to "Type 2", that is, if it is determined that it corresponds to "Type 3" (S10: NO), the process proceeds to S14.

[0058] Next, in S11, the CPU 21 compares the emotion values for each basic emotion calculated in S5 for the information-providing location that is the current evaluation target, and identifies the basic emotion whose emotion value is equal to or greater than the second threshold as the posted emotion (the basic emotion to which it belongs) of the information-providing location that is the current evaluation target. If there are multiple basic emotions whose emotion values are equal to or greater than the second threshold, all corresponding ones are identified as the posted emotions of the information-providing location that is the current evaluation target. However, it may be set to a predetermined number (for example, the top two) in descending order of emotion value. The second threshold is, for example, 25% of the total value obtained by summing up all the emotion values of each emotion. For example, in the example of 'Type 2' shown in FIG. 8, "joy" and "expectation" will be identified as the posted emotions (the basic emotions to which they belong).

[0059] Next, in S12, the CPU 21 determines whether it is possible to identify an applied emotion (secondary emotion) from the combination of the basic emotions identified in S11. Here, the applied emotion is an emotion generated by a combination of basic emotions and is a more detailed (specific) emotion than the basic emotion. In this embodiment, the applied emotion is identified only when the emotion classification of the information-providing location that is the current evaluation target corresponds to 'Type 2', and is basically not identified for 'Type 1' or 'Type 3'.

[0060] Here, FIG. 9 is a diagram showing the correlation relationship of eight types of basic emotions derived from the calculation result of calculating the basic emotions included in each text data by performing emotion analysis by machine learning on the text data of a large number of randomly extracted posted texts. That is, in FIG. 9, the basic emotions with a high correlation tend to have a high emotion ratio at the same time in the same text data (the tendencies of the emotions are similar and they are emotions that are likely to appear at the same time), and the basic emotions with a low correlation tend to be less likely to have a high emotion ratio at the same time in the same text data (the tendencies of the emotions are different and they are emotions that are difficult to appear at the same time).

[0061] Then, for combinations of basic emotions with a certain level of correlation or higher, the emotion that arises from that combination is defined as an applied emotion. FIG. 10 is an example showing the correspondence between combinations of basic emotions and the applied emotions that arise from those combinations. Note that the example shown in FIG. 10 is merely an example, and the combinations of basic emotions and the types of applied emotions are not limited to the example shown in FIG. 10. Also, the number of basic emotions to be combined may be three or more.

[0062] Then, for example, if the combination of basic emotions identified in S11 above includes the combination shown in FIG. 10, it is determined that the applied emotion can be identified (S12: YES), and the applied emotion corresponding to the combination of basic emotions identified in S11 is additionally identified as the posted emotion (belonging to the applied emotion) at the information-providing location (S13). On the other hand, if the combination shown in FIG. 10 does not exist in the combination of basic emotions identified in S11, it is determined that the applied emotion cannot be identified (S12: NO). However, the identification of the applied emotion may be limited only to cases where the total of the emotion values of the basic emotions to be combined satisfies a condition that the total is equal to or higher than a threshold value (for example, 65% or more of the total value obtained by summing up all the emotion values of each emotion). Also, when the number of basic emotions identified in S11 is three or more, multiple applied emotions may be identified. On the other hand, when the number of basic emotions identified in S11 is only one, there is basically no case where an applied emotion is identified.

[0063] However, the method for identifying the applied emotion is not limited to the above method. For example, a correlation relationship may be defined in advance between eight types of basic emotions and 24 types of applied emotions, and the applied emotion with the highest correlation to the basic emotions identified in S11 may be identified.

[0064] After that, in S9, the CPU 21 stores in the distribution information DB 7, as "posted emotion" regarding the information providing location that is the target of this evaluation, the basic emotion specified in S11 and the applied emotion (only when the applied emotion is specified). Further, the CPU 21 also generates a bar graph showing the emotion value for each basic emotion calculated in S5, and a line graph showing the transition of the emotion value over time for the basic emotion whose emotion value specified in S11 is above the second threshold, and stores them in the distribution information DB 7 as information regarding the "posted emotion" regarding the information providing location that is the target of this evaluation. As described above, the distribution information DB 7 stores various types of information including information regarding "posted emotion" regarding the information providing locations that are the targets of information provision across the country (Fig. 4).

[0065] On the other hand, in S14 which is executed when it is determined that the emotion classification of the information providing location that is the target of this evaluation is "Type 3", the CPU 21 determines that there is no prominent emotion regarding the information providing location that is the target of this evaluation, that is, there is no particularly strong emotion in the whole posted text, there is no bias in emotion, and the emotion cannot be specified. Therefore, the CPU 21 specifies "no emotion (lack of emotion)" as the posted emotion (the basic emotion to which it belongs) regarding the information providing location that is the target of this evaluation.

[0066] After that, in S9, the CPU 21 stores "no emotion" in the distribution information DB 7 as the "posted emotion" regarding the information providing location that is the target of this evaluation.

[0067] Subsequently, in the information providing system 1, the information providing processing program executed by the information providing server 3 and the communication terminal 5 will be described with reference to Fig. 11. Fig. 11 is a flowchart of the information providing processing program according to this embodiment. Here, the information providing processing program is a program that is executed after a predetermined application program for obtaining information on the information providing location is started in the communication terminal 5, and provides information regarding the information providing location to the user. Note that the program shown in the flowchart in Fig. 11 below is stored in the RAM or ROM provided in the information providing server 3 and the communication terminal 5, and is executed by the CPU 21 or the CPU 31.

[0068] First, an information provision processing program executed by the CPU 31 of the communication terminal 5 will be described with reference to FIG. 11. In S21, the CPU 31 starts a predetermined application program (hereinafter referred to as an information provision application) for obtaining information on the information provision location. Note that the information provision application may be a navigation application or a dedicated application program different from the navigation application. It is assumed that the information provision application has been downloaded from a web server or the like in advance and installed in the communication terminal 5.

[0069] Here, when the information provision application is started in the communication terminal 5, first, a map image around the current location is displayed on the display 36 (S22). Note that map display data for displaying the map image 51 is acquired from the information provision server 3. The map image 51 displayed on the display 36 can be freely scaled or the display target area can be changed based on user operations.

[0070] Next, in S23, the CPU 31 transmits a request signal to the information provision server 3 requesting information regarding the information provision location included in the map image that is the display target on the display 36 at the current time. Note that the request signal includes a terminal ID for identifying the transmitting communication terminal 5 and a location ID (a location name or position coordinates may be used instead of the location ID) for identifying the information provision location included in the map image that is the display target on the display 36 at the current time.

[0071] Thereafter, in S24, the CPU 31 receives the information transmitted from the information provision server 3 in response to the request signal transmitted in S23. Note that the information received in S24 is information regarding the information provision location included in the map image that is the display target on the display 36 at the current time, particularly information regarding the type and magnitude (emotion value) of the "posted emotion" specified by the above-described emotion analysis processing program (FIG. 6).

[0072] Subsequently, in S25, the CPU 31 displays an icon indicating the existence of an information providing point at the position where the information providing point exists in the map image around the current position displayed on the display 36. The icon also indicates the type of the posted emotion and the magnitude of the emotion of the information providing point.

[0073] Here, FIG. 12 is a diagram showing an example of the icon displayed in S25. As shown in FIG. 12, a map image 51 is displayed on the display 36, and an icon 52 is further displayed at the position where the information providing point exists in the map image 51. The appearance of the icon 52 mimics a face, and there are three types of expressions, and the type of the posted emotion of the information providing point is indicated by the difference in the expressions. In the present embodiment, in the above-described emotion analysis processing program (FIG. 6), "posted emotion" is specified by eight types of basic emotions and twenty-four types of applied emotions, respectively. However, the icon 52 does not distinguish up to the specific type of emotion, and uses two types, positive emotion (positive emotion) and negative emotion (negative emotion), as judgment elements to indicate whether the emotion of the poster is closer to positive emotion or negative emotion, or whether it is neutral (neutral) that is neither. However, the type of the icon 52 may be increased to notify up to the specific type of emotion.

[0074] As an example, if the basic emotion specified as the posted emotion includes either "joy" or "trust", it is positive. If the basic emotion specified as the posted emotion includes any of "aversion", "anger", "fear", or "sadness", it is negative. If the basic emotion specified as the posted emotion includes either "expectation" or "surprise" or is "unemotional", it is neutral. In addition, when corresponding to a plurality of emotion categories (for example, positive and neutral), the emotion category corresponding to the basic emotion with the highest emotion value is selected. In addition, the emotion value for each basic emotion can be obtained from the information providing server 3 as a bar graph (FIG. 4).

[0075] Furthermore, if the appearance of icon 52 is “Positive”, it will show a friendly expression; if it is “Negative”, it will show an angry expression; and if it is “Neutral”, it will show a blank expression. Therefore, when the user visually recognizes icon 52, they can easily grasp the posted emotion at the information-providing location. Also, the display size of icon 52 changes according to the magnitude of the posted emotion. The greater the magnitude of the posted emotion, the larger the display size. Specifically, the magnitude of the emotion is determined by the emotion value of the basic emotion (to which the posted emotion belongs) identified as the posted emotion. For example, if the sum of the emotion values of the basic emotion identified as the posted emotion is greater than or equal to the first value, the size is considered large; if the sum of the emotion values of the basic emotion is less than the first value but greater than or equal to the second value, the size is considered medium; and if the sum of the emotion values of the basic emotion is less than the second value, the size is considered small. In addition to changing the display size of icon 52, it is also possible to change the display color. For information-providing locations where the posted emotion cannot be determined, it is acceptable not to display icon 52, or to display a “Neutral” icon 52.

[0076] Also, icon 52 displayed on the map image 51 is a selection target for the user. In S26, the CPU 31 determines whether it has received an operation for the user to select any of the icons 52 displayed on the map image 51 based on the signal from the input operation unit 37.

[0077] When it is determined that the CPU has received an operation for the user to select any of the icons 52 displayed on the map image 51 (S26: YES), the process proceeds to S27. On the other hand, when it is determined that the CPU has not received an operation for the user to select any of the icons 52 displayed on the map image 51 (S26: NO), the information-providing processing program ends.

[0078] Subsequently, in S27, the CPU 31 transmits a request signal to the information providing server 3 to request more detailed information regarding the information providing point corresponding to the icon 52 selected by the user. Note that the request signal includes a terminal ID for identifying the source communication terminal 5 and a location ID for identifying the information providing point corresponding to the icon 52 selected by the user (the location name or location coordinates may be used instead of the location ID).

[0079] Thereafter, in S28, the CPU 31 receives the information transmitted from the information providing server 3 in response to the request signal transmitted in S27. Note that the information received in S28 is more detailed information regarding the information providing point corresponding to the icon 52 selected by the user.

[0080] Next, in S29, the CPU 31 displays, on the display 36, more detailed information regarding the information providing point corresponding to the icon 52 selected by the user based on the information received in S28. Note that the information to be displayed includes, in addition to the basic emotions and types of applied emotions specified as "posted emotions" by the aforementioned sentiment analysis processing program (Fig. 6), a bar graph showing the emotion values for each basic emotion calculated in S5, and also includes a line graph showing the transition of the emotion values with respect to time for the basic emotions.

[0081] Here, Fig. 13 shows an example of the information providing screen 53 displayed on the display 36 in S29. In the example shown in Fig. 13, the information providing screen 53 includes, for example, the name of the information providing point, an exterior photo, information regarding the details of the point such as business hours and contact information, and in addition to the various types of basic emotions and applied emotions specified as "posted emotions", a bar graph showing the emotion values for each basic emotion calculated in S5, and a line graph showing the transition of the emotion values with respect to time for the basic emotions are displayed.

[0082] Specifically, for the "posted emotion", the type of emotion specified from among the eight basic emotions and 24 applied emotions in the above-described emotion analysis processing program (Figure 6) is displayed. However, the applied emotions are not necessarily displayed, and are limited to the case where the applied emotions are specified in S13. Also, when "no emotion (without emotion)" is specified (S14), that fact is displayed. Also, the bar graph shows a comparison of the magnitudes (emotion values) of emotions for each of the eight basic emotions. By referring to the bar graph, the user can grasp, in addition to the basic emotion specified as the "posted emotion", the extent to which other basic emotions are included, and can grasp the more detailed emotional trends. On the other hand, the line graph shows the transition of the emotion value with respect to time in a rectangular coordinate system with the time axis on the horizontal axis and the emotion value on the vertical axis, targeting the basic emotion specified as the "posted emotion" among the eight basic emotions, particularly at the information providing point. When multiple basic emotions are specified as the "posted emotion", the transition of the emotion value is displayed for each of the multiple basic emotions. By referring to the line graph, the user can particularly grasp the transition of the emotion with respect to time, and can also grasp the time suitable for visiting. Note that the transition of the emotion value with respect to the date or day of the week instead of the time may be displayed.

[0083] Note that the information providing screen 53 shown in FIG. 13 is merely an example, and any display mode may be used as long as the basic emotions and applied emotions specified as the "posted emotion" are displayed so that the user can grasp them. Also, the display of the bar graph and the line graph is not essential and may be excluded from the display target. By the user visually recognizing the information providing screen 53 shown in FIG. 13, the user can obtain an accurate evaluation based on the posted text for the specified point.

[0084] Next, the information providing processing program executed by the CPU 21 of the information providing server 3 will be described. Note that each of the following processes S31 to S36 starts at the timing when the corresponding information from the communication terminal 5 is received. Therefore, the execution order of each step is not necessarily in the order of the smaller step numbers.

[0085] First, in S31, the CPU 21 receives a request signal for information transmitted from the communication terminal 5. Note that the request signal includes a terminal ID for identifying the source communication terminal 5 and a location ID for identifying the information-providing location corresponding to the icon 52 selected by the user (a location name or position coordinates may be used instead of the location ID).

[0086] After that, in S32, the CPU 21 extracts information regarding the requested information-providing location from the distribution information DB 7 based on the request signal received in S31. Note that as described above, the distribution information DB 7 stores various types of information including information regarding "posted feelings" for information-providing locations targeted for information provision across the country (Fig. 4), but in S32, only the type of "posted feelings" and the magnitude of the feelings (feeling value) are extracted.

[0087] Subsequently, in S33, the CPU 21 transmits the type of "posted feelings" and the magnitude of the feelings (feeling value) as information regarding the information-providing location extracted in S32 to the communication terminal 5, which is the source of the request signal received in S31. After that, on the communication terminal 5 that has received the information, the posted feelings of the information-providing location are displayed by the icon 52 on the map image 51 as described above (Fig. 12).

[0088] Next, in S34, the CPU 21 receives a request signal for detailed information transmitted from the communication terminal 5. Note that the request signal includes a terminal ID for identifying the source communication terminal 5 and a location ID for identifying the information-providing location corresponding to the icon 52 selected by the user (a location name or position coordinates may be used instead of the location ID).

[0089] After that, in S35, the CPU 21 extracts information regarding the information providing location requested based on the request signal received in S34 from the distribution information DB 7. In the distribution information DB 7, in addition to the types of basic emotions and applied emotions specified as "posted emotions" for the information providing locations targeted for information provision across the country as described above, various information including a bar graph showing the emotion values for each basic emotion calculated in S5 and information regarding a line graph showing the transition of emotion values over time for the basic emotions is stored (Fig. 4), and in S35, basically all of this information is extracted.

[0090] Subsequently, in S36, the CPU 21 transmits detailed information regarding the information providing location extracted in S35 to the communication terminal 5 which is the transmission source of the request signal received in S34. After that, in the communication terminal 5 that has received the information, information regarding the information providing location is output as described above (Fig. 13).

[0091] As described in detail above, in the information providing system 1, the information providing server 3, and the communication terminal 5 according to the present embodiment, a posted text posted on the network is acquired together with location information specifying the location associated with the posted text (S2), and by analyzing the acquired posted text, the posted emotion which is the emotion of the poster who posted the posted text is predicted (S3), and the predicted posted emotions are classified and aggregated for each location associated with the posted text that is the analysis source, and the posted emotion is specified for each location (S8, S11, S13, S14), and the posted emotion at the designated location is displayed on the screen (S25, S29). On the other hand, in specifying the posted emotion, in addition to which of the basic emotions into which the posted emotion is classified into multiple types it belongs to, when a predetermined condition is satisfied, it is also specified which of the applied emotions generated by a combination of different types of basic emotions it belongs to, and the basic emotion and the applied emotion specified as belonging to the posted emotion are each displayed. Therefore, it is possible to provide the user with information regarding the posted emotion at that location in a manner that specifies the posted emotion at that location down to more specific types of emotions for each location. As a result, the user can obtain a more accurate evaluation based on the posted text for the location. Also, while specifying the type and magnitude of the posted emotion for each location (S5, S8, S11, S13, S14), a map image of a predetermined area is displayed on the screen, and the icon 52 is displayed at the position of the location included in the map image, and the type and magnitude of the posted emotion at the location are indicated by the appearance of the icon 52 (S25). Therefore, a user who views the map image can easily and visually grasp the type and magnitude of the posted emotion at each location included in the map image by means of the icon. Also, an emotion value is calculated (S5) which is the amount obtained by classifying and then aggregating the posted emotions predicted by emotion analysis (S3) performed on the posted text linked to each location, for each of a plurality of types of basic emotions. If the difference between the emotion value of the most highly emotional basic emotion and the emotion value of the second most highly emotional basic emotion is equal to or greater than the first threshold value, the most highly emotional basic emotion is specified as the basic emotion to which the posted emotion belongs, and the applied emotion is not specified (S8). If the difference between the emotion value of the most highly emotional basic emotion and the emotion value of the second most highly emotional basic emotion is less than the first threshold value, the basic emotion with an emotion value equal to or greater than the second threshold value is specified as the basic emotion to which the posted emotion belongs, and the applied emotion is also specified (S11, S13). Therefore, when the posted emotion includes a plurality of types of basic emotions, that is, when it is difficult to clearly recognize what kind of posted emotion it is only from the basic emotions, the user can grasp the posted emotion more accurately by also specifying and providing the more detailed applied emotion. Also, if the difference between the emotion value of the most highly emotional basic emotion and the emotion value of the second most highly emotional basic emotion is less than the first threshold value, the applied emotion generated from the combination of basic emotions with an emotion value equal to or greater than the second threshold value is specified as the applied emotion to which the posted emotion belongs (S13). Therefore, for a case where the posted emotion includes a plurality of types of basic emotions, it is possible to accurately specify the applied emotion included in the posted emotion by specifying and providing the applied emotion generated from the combination of the relatively highly emotional basic emotions among them.

[0092] Note that the present invention is not limited to the above-described embodiment, and it goes without saying that various improvements and modifications are possible without departing from the gist of the present invention. For example, in the present embodiment, it is specified which of the eight basic emotions and 24 applied emotions the posted emotion at the information-providing location belongs to. However, the basic emotions are not limited to the above eight emotions, and the applied emotions are not limited to the above 24 emotions either.

[0093] Also, in the present embodiment, the applied emotions are specified only when the emotion classification at the information-providing location corresponds to 'Type 2', and basically not specified for 'Type 1' or 'Type 3'. However, even when it corresponds to 'Type 1' or 'Type 3', the applied emotions may be specified. For example, in the case of 'Type 1', it is possible to select and specify from the applied emotions that have a high correlation with the basic emotion with the highest emotion value.

[0094] Also, in the present embodiment, an example in which the communication terminal 5 is applied to a smartphone has been described. However, if it has a function of outputting information regarding the information-providing location, it can also be applied to other types of communication terminals. For example, it can be applied to mobile phones, tablet terminals, personal computers, navigation devices which are in-vehicle devices, etc. Also, when applying it to other than the navigation device, it can be implemented even in situations where the user moves other than by car, for example, in situations where the user moves on foot.

[0095] Also, in the present embodiment, the information-providing server 3 is configured to perform the emotion analysis processing program (Figure 6), but a part of the processing may be executed by the communication terminal 5.

Explanation of Reference Numerals

[0096] 1... Information-providing system (posted emotion prediction system), 2... Information-providing center, 3... Information-providing server, 4... User, 5... Communication terminal, 6... Communication network, 7... Distribution information DB, 8... SNS server, 9... Storage DB, 11... Server control unit, 13... Posted text information DB, 36... Display, 41... Communication terminal control unit, 51... Map image, 52... Icon, 53... Information-providing screen

Claims

1. Post text information acquisition means for acquiring a post text posted on a network together with location information specifying a location associated with the post text; Emotion prediction means for predicting an emotion of a poster who posted the post text by analyzing the post text acquired by the post text information acquisition means; Location emotion specifying means for classifying and aggregating the post emotions predicted by the emotion prediction means for each location associated with the post text serving as an analysis source, and specifying the post emotion for each location; Post emotion display means for displaying the post emotion at a specified location on a screen, and having: The location emotion specifying means, in addition to which of a plurality of types of basic emotions the post emotion belongs to, also specifies which of the applied emotions generated by a combination of different types of the basic emotions the post emotion belongs to when a predetermined condition is satisfied; The post emotion display means is an information providing system that displays the basic emotion and the applied emotion to which the post emotion is determined to belong.

2. The location emotion specifying means specifies the type and magnitude of the post emotion; Displays a map image of a predetermined area on the screen, and the specified location is a location included in the map image, and The post emotion display means Displays an icon at the position of the location included in the map image, and The information providing system according to claim 1, wherein the type and magnitude of the post emotion at the location are indicated by the appearance of the icon.

3. The location emotion specifying means Calculates an emotion value, which is the sum of the post emotions predicted by the emotion prediction means performed on the post text associated with each location, after classifying them for each of a plurality of types of basic emotions; If the difference between the emotion value of the most highly emotional basic emotion and the emotion value of the second most highly emotional basic emotion is equal to or greater than a first threshold value, the most highly emotional basic emotion is specified as the basic emotion to which the post emotion belongs, and no applied emotion is specified; If the difference between the emotion value of the most highly emotional basic emotion and the emotion value of the second most highly emotional basic emotion is less than the first threshold value, the basic emotion with an emotion value equal to or greater than a second threshold value is specified as the basic emotion to which the post emotion belongs, and the applied emotion is also specified. The information providing system according to claim 1 or claim 2.

4. The location emotion specifying means The information providing system according to claim 3, wherein if the difference in emotional value between the most emotionally valuable basic emotion and the second most emotionally valuable basic emotion is less than the first threshold value, an applied emotion generated from a combination of basic emotions with an emotional value of the second threshold value or more is specified as the applied emotion to which the posted emotion belongs.

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