JP4800187B2 - Evaluation information management system, evaluation information management program, and evaluation information management method - Google Patents

Description

  The present invention relates to an evaluation information management system, an evaluation information management program, and an evaluation information management method for managing evaluation information representing an evaluation of a contributor who posts information, particularly even if the number of contributors increases. The present invention relates to an evaluation information management system, an evaluation information management program, and an evaluation information management method capable of easily confirming a poster's evaluation without deteriorating operability and improving readability.

  2. Description of the Related Art Conventionally, an electronic bulletin board service that publishes information provided by users on the Internet has been used. For example, an electronic bulletin board service is provided in which various users evaluate restaurants and display the ranking of restaurants in descending order of evaluation.

  Furthermore, in such information exchange between users, an information providing system that ensures the accuracy, popularity, and freshness of information has been devised (see, for example, Patent Document 1). Specifically, in this information providing system, when the information posted by the user is incorrect, the information correction by the user is accepted.

  In addition, the user can vote for the evaluation on the posted information. This voting data is deleted after a predetermined period in order to keep information fresh. When there is an information browsing request from the user, the evaluations made on the posted information are totaled, and the rankings of the posted information are displayed in descending order of evaluation.

  In addition, on the output screen of posted information, an evaluation button for viewing the evaluation of the poster who posted the information is provided, and the user can click the evaluation button with a mouse or the like to evaluate the poster. Can be viewed.

JP 2005-157495 A

  However, in the prior art represented by the above-mentioned Patent Document 1, in order to see the evaluation of the poster, it is necessary to output another screen by clicking the evaluation button provided on the posted information output screen. There was a problem that the viewability was bad.

  This is not a problem when the number of contributors is small, but when the number of contributors increases, the evaluation buttons provided on the output screen of the information posted by each contributor are respectively displayed. There was a problem that the operability deteriorated because it was necessary to click.

  Therefore, even if the number of contributors increases, it is desirable to develop a technology that can easily check the contributor's evaluation without deteriorating operability, and can improve the readability. It was.

  The present invention has been made to solve the above-described problems caused by the prior art, and even if the number of contributors increases, the user's evaluation can be easily confirmed without deteriorating the operability. An object of the present invention is to provide an evaluation information management system, an evaluation information management program, and an evaluation information management method that can improve the viewability.

In order to solve the above-described problems and achieve the object, the present invention is an evaluation information management system for managing evaluation information indicating an evaluation for a contributor who posts information, and the information posted by the contributor is posted. Storage means for storing the information in association with the identification information of the person, support number counting means for counting the number of times that the viewer of the information posted by the poster has performed an operation to support the information as an evaluator, and the posting The total number of information posted by the contributor for each contributor, and the number of unsupported counts that count the number of times the viewer of the information posted by the user performed an operation that does not support the information as an evaluator. Posting number totaling means for totaling the number of posts, and the total number of supporting totals for totaling the number of support for the information posted by the poster for each contributor, and for each contributor posted No information The total number of support is the ratio of the total number of support to the total number of the total number of support and total number of unsupported for each contributor Support rate calculation means for calculating a rate, and for each contributor, an icon of a color according to the size of one of the number of posts and the support rate and including characters according to the size of the other An icon information generation unit that generates information, and an information output unit that outputs the information of the icon generated by the icon information generation unit together with the identification information of the poster corresponding to the icon .

Further, according to the present invention, in the above invention, a support rate history storage unit that stores a history of the support rate calculated by the support rate calculation unit, a past support rate stored in the support rate history storage unit, and the support A support rate fluctuation specifying unit that specifies a change in the support rate based on the new support rate calculated by the rate calculating unit, and the icon generated by the icon information generating unit is generated by the support rate change specifying unit. It includes a symbol representing the specified variation in the support rate .

Further, the present invention, in the above invention, further comprises a contributor ranking creating means for creating a contributor ranking in which the corresponding icons and the identification information are arranged in order from the contributor having the largest product of the number of posts and the support rate. The information output means outputs the poster ranking created by the poster ranking creation means .

Further, in the present invention, the information posted by the contributor is word-of-mouth information for a store in the above invention, and each of the designated icons is designated when a plurality of icons are designated among the icons output by the information output means. Search means for searching for word-of-mouth information for a common store from the word-of-mouth information of each contributor corresponding to the icon, wherein the information output means outputs the word-of-mouth information searched by the search means .

Further, the present invention provides level determining means for determining the level of the poster based on the support and non-support operations by the evaluator performed on the information posted by the poster, and information posted by the poster Generating means for displaying information in a display form corresponding to the level determined by the level determining means for the poster, and the information output means is generated by the generating means It is characterized by outputting information .

Further, the present invention is characterized in that, in the above invention, the level of the contributor is determined based on the level of the evaluator who performed the support or non-support operation .

Further, the present invention is an evaluation information management program for managing the evaluation information indicating an evaluation for the contributor to post information to a computer, the computer, posts, reviews and information identification information of the author Storage processing means for storing the information in the storage device in association with each other, the support number counting means for counting the number of times that the viewer of the information posted by the contributor has performed an operation to support the information as an evaluator as the support number, Unsupported number counting means for counting the number of times a viewer of posted information performed an operation that does not support the information as an evaluator as the number of unsupported posts, which is the total number of information posted by the poster for each poster information posts aggregation means for aggregating the number, for each author, the author can support total aggregate unit that aggregates the total number of support numbers for post information, for each author, the author has posted Unsupported total number counting means for counting the total number of unsupported, the ratio of the total number of the supported number out of the total number of the total number of the supported number and the total number of unsupported for each contributor Support rate calculating means for calculating a support rate, for each contributor, an icon of a color corresponding to the size of one of the number of posts and the support rate, and including a character corresponding to the size of the other An icon information generating unit that generates information, and an information output unit that outputs the icon information generated by the icon information generating unit together with the identification information of the poster corresponding to the icon .

Further, the present invention is an evaluation information management method in which a computer system manages evaluation information indicating an evaluation for a poster who posts information, and stores information posted by a poster in association with identification information of the poster. A storage processing step stored in the device, a support number counting step in which the number of times a viewer of the information posted by the contributor performs an operation to support the information as an evaluator is counted as a support number, and information posted by the contributor The number of submissions that is the total number of information posted by the poster for each poster, and the number of submissions that are not supported as the evaluator. Total number of posts to be aggregated, number of support totals for total number of support for information posted by the poster for each contributor, and number of unsupport for information posted by the poster for each poster Calculate the support rate, which is the ratio of the total number of support units out of the total number of the total number of support units and the total number of non-support units for each poster The support rate calculation step to perform, and for each contributor, generates information of an icon that is a color icon according to the size of one of the number of posts and the support rate and that includes characters according to the size of the other The computer system executes each step of the icon information generation step to output and the information output step of outputting the icon information generated by the icon information generation step together with the identification information of the poster corresponding to the icon. Features.

According to the present invention, an icon having a color according to the size of one of the number of posts and the support rate and including a character according to the size of the other is output together with identification information for identifying the poster. Therefore, by using the above icons, even if the number of contributors increases, the user can easily check the contributor's evaluation without deteriorating the operability, improving the readability There is an effect that can be made.

  Exemplary embodiments of an evaluation information management system, an evaluation information management program, and an evaluation information management method according to the present invention will be described below in detail with reference to the accompanying drawings. Here, the case where the evaluation target of the evaluation information to be managed is a restaurant will be described as an example. However, the evaluation target is not limited to this, and the present invention is similarly applied to other evaluation targets. Can be applied.

  First, the configuration of the information providing system according to the present embodiment will be described. FIG. 1 is a diagram illustrating the configuration of the information providing system 20 according to the present embodiment. The information providing system 20 shown in FIG. 1 is a system that accepts restaurant evaluation information from a user as word-of-mouth information and opens the accepted word-of-mouth information to other users.

  In addition, the posted information totaling system 20 receives evaluations from other users on the word-of-mouth information posted by the poster, and generates evaluation ranking information that ranks the poster based on the rating. And when the output request | requirement of a poster's evaluation ranking is received from a user, the information is output to the user terminal which a user uses.

  In this evaluation ranking, the ranking of each contributor, the name of each contributor, and an icon indicating the evaluation of each contributor are output in association with each other and displayed on the same screen on the user terminal.

  Therefore, the user does not need to output other screens to view each poster's evaluation, and even if the number of posters increases, the operability does not deteriorate, The evaluation can be easily confirmed, and the visibility of the evaluation is improved.

  As shown in FIG. 1, the information providing system 20 is connected to user terminals 10a to 10c via a network 30 (Internet, public line network, etc.). The user terminals 10a to 10c are information terminals such as personal computers and mobile phones.

  The user operates the user terminals 10a to 10c to connect to the information providing system 20, and browses word-of-mouth information and various ranking information, posts word-of-mouth information, and evaluates word-of-mouth information posted by other users.

  Further, the user terminals 10a to 10c are provided with a GPS (Global Positioning System) function for detecting the current position of the user. The user terminals 10a to 10c receive the restaurant information of the area corresponding to the current position from the information providing system 20 by transmitting information on the current position of the user detected using the GPS function to the information providing system 20. .

  The information providing system 20 is configured by connecting an information providing server 40, an information storage server 50, and an information totaling server 60 via a network 70 (LAN or the like).

  The information providing server 40 is a server that outputs requested information to the user terminals 10a to 10c when receiving output requests for various information such as word-of-mouth information from the user terminals 10a to 10c. The information providing server 40 includes a communication processing unit 41, a storage unit 42, an information providing processing unit 43, and a control unit 44.

  The communication processing unit 41 is a network interface that communicates with the user terminals 10 a to 10 c via the network 30 or with the information storage server 50 and the information totaling server 60 via the network 70.

  The storage unit 42 is a storage device such as a hard disk device. The storage unit 42 stores content data 42a and user data 42b.

  The content data 42a is information acquired from the information storage server 50 when the information providing server 40 acquires information from the information storage server 50 and provides the user terminals 10a to 10c with various screens to be output to the user terminals 10a to 10c. Is content data for embedding and configuring. The user data 42b is data that stores a user ID, a password, and the like of a user who logs in to the information providing service.

  The information provision processing unit 43 performs login management of a user who uses this information provision service, and when receiving an output request for information such as word-of-mouth information from the user terminals 10a to 10c, the information provision processing unit 43 sends the requested information to the user terminal 10a. To 10c.

  Specifically, the information provision processing unit 43 corresponds to the region input by the user using the user terminals 10a to 10c or the current position of the user detected by the GPS function provided in the user terminals 10a to 10c. The output request of the restaurant information of the area to receive is received.

  FIG. 2 is a diagram illustrating an example of a top screen 100 that receives a restaurant information output request. The top screen 100 includes a search reception area 101, a region designation reception area 102, and a poster ranking display request reception area 103.

  The search reception area 101 is a reception area for receiving search conditions for narrowing down restaurants such as keywords and regions, genres, budgets, atmospheres, and coupons. The keyword is a keyword when a search is performed on restaurant information. The area is an area where restaurants are located. The genre is a genre of cuisine of restaurants such as Japanese, Western and Chinese. The budget is the budget amount for cooking. The atmosphere is suitable for shops such as dates and banquets. A coupon designates the presence or absence of a coupon.

  The user can search for restaurant information by specifying such information and clicking search button 104 with a mouse or the like. In addition, when detecting a user's present location using the GPS function of user terminal 10a-10c, the search of the restaurant information of the area corresponding to a current position is performed without designation | designated of an area.

  The area designation receiving area 102 is a receiving area for receiving area designation by clicking with a mouse or the like when narrowing down shops. The contributor ranking display request receiving area 103 is a receiving area for receiving a contributor ranking display request described later from the user. The user can display the poster ranking on the user terminals 10a to 10c by clicking the display button 105 with a mouse or the like.

  Here, the contributor ranking is a ranking in which the evaluation results evaluated by other users with respect to the word-of-mouth information posted by the contributor are aggregated and the contributors are ranked in descending order of evaluation.

  When such a top screen 100 receives a restaurant information search request including a region and other narrowing conditions, the information provision processing unit 43 is transmitted to the information storage server 50 by the user terminals 10a to 10c. The restaurant information corresponding to the narrowing-down condition is requested to be transmitted.

  And the information provision process part 43 receives the restaurant information transmitted by the information storage server 50, and outputs the received restaurant information to the user terminals 10a-10c. This restaurant information includes information on restaurant rankings in which the restaurant information is arranged in the order of restaurants with the highest evaluation in the word-of-mouth information posted by each contributor on the area he / she is good at.

  In addition, here, in the review information posted by each contributor about the area he is good at, the restaurant ranking information in which the restaurant information is arranged in the order of the restaurant with the highest evaluation is output. It is good also as outputting the information of the restaurant ranking in which the restaurant information was arranged in the order of the restaurant with the highest evaluation in the review information posted by the poster about the genre of the restaurant that he is good at.

  FIG. 3 is a diagram illustrating an example of the regional restaurant ranking output screen 110. In the example of FIG. 3, the restaurant ranking 111 corresponding to the area “Roppongi” designated from the user terminals 10a to 10c is shown. This restaurant ranking 111 includes store name [genre], region, point, and evaluation information.

  The store name [genre] is information on the restaurant name and genre of the restaurant. A hyperlink is set in this item, and detailed word-of-mouth information of the store can be output by clicking the store name [genre] with a mouse or the like. This word-of-mouth information will be described in detail later.

  The region is information on a region corresponding to each restaurant, and is information on a region designated by the user terminals 10a to 10c. The point is word-of-mouth information most supported by the user among the word-of-mouth information posted. Evaluation is information of the average value of the evaluation of the restaurant evaluated in five steps by the contributor of the word-of-mouth information. Information of each restaurant is arranged in order of increasing average value.

  Moreover, the information provision process part 43 performs the process which further narrows down the restaurant information output to the restaurant ranking 111 as well as the area. In the example of FIG. 3, a narrowing condition 112 (genre, budget, atmosphere, coupon) for narrowing down restaurant information is output.

  In this case, when the information provision processing unit 43 receives the information of the narrowing-down condition 112 specified by the user clicking with the mouse or the like from the user terminals 10 a to 10 c, the information providing processing unit 43 sends the user terminals 10 a to 10 c to the information storage server 50. In addition to the information on the area transmitted by, the information on the restaurant ranking 111 corresponding to the filtering condition 112 is further requested.

  And the information provision process part 43 receives the information of the restaurant ranking 111 transmitted by the information storage server 50, and outputs the received information to user terminal 10a-10c.

  As described with reference to FIG. 3, when a store name [genre] in which a hyperlink is set is clicked with a mouse or the like, detailed word-of-mouth information about the restaurant is output. FIG. 4 is a diagram illustrating an example of the word-of-mouth information output screen 120.

  This review information output screen 120 includes basic information 121, latest review information 122, useful review information 123, evaluation distribution 124, budget distribution 125, atmosphere distribution 126, and gender / generation information 127.

  The basic information 121 is basic information on restaurants. Specifically, the basic information 121 includes information on word-of-mouth, average budget, transportation, address, telephone, and atmosphere. The word-of-mouth communication is information on the average value of restaurants evaluated in five stages by the word-of-mouth information contributor and the number of word-of-mouth information posted (number of word-of-mouth).

  The average budget is information on the average value of the budget amount of the restaurant registered by the reviewer. The transportation means is information on transportation means that is most convenient for going to restaurants. The address and telephone are information on the restaurant address and telephone number. The atmosphere is information on the atmosphere of the restaurant most frequently registered by the poster.

  The latest review information 122 is the latest review information among the review information posted by the contributor. Moreover, the useful word-of-mouth information 123 is information (for example, top ten word-of-mouth information etc.) with high evaluation among word-of-mouth information evaluated as useful by users other than the poster.

  In addition, when viewing all the word-of-mouth information regarding this restaurant, all the word-of-mouth information is displayed by clicking on a character string with a hyperlink “view all word of mouth” set with a mouse or the like.

  The evaluation of the review information is the latest review information 122, the helpful review information 123, or the evaluation buttons 128a to 128d provided in the display area of each review information when all the review information is displayed (“Is this review helpful?” This is done by counting the number of times the “Yes” button or “No” button) corresponding to “?” Is clicked with the mouse or the like.

  Specifically, when the evaluation buttons 128 a to 128 d are clicked with a mouse or the like, the information provision processing unit 43 transmits the information to the information storage server 50. The information storage server 50 that has received this information counts the number of times the evaluation buttons 128a to 128d ("Yes" button or "No" button) are clicked with a mouse or the like in association with each piece of word-of-mouth information. Store information.

  The evaluation distribution 124 is information on the distribution of evaluation for this restaurant registered by the contributor of the word-of-mouth information. The budget distribution 125 is information on the budget amount distribution of the restaurant registered by the contributor of the review information. The atmosphere distribution 125 is information on the distribution of the atmosphere of this restaurant registered by the contributor of the review information. The gender / generation information 127 is information on the distribution of the gender / generation of the poster who posted the word-of-mouth information to this restaurant.

  By the way, the restaurant ranking 111 on the regional restaurant ranking output screen 110 shown in FIG. 3 and the basic information 121 on the word-of-mouth information output screen 120 are hyperlinks for shifting to a posting acceptance screen that accepts posting of word-of-mouth information. A character string “register word-of-mouth information” is set.

  A user who posts word-of-mouth information can click the character string with a mouse or the like to output a posting acceptance screen and make a posting. FIG. 5 is a diagram illustrating an example of the posting acceptance screen 130.

  This posting acceptance screen 130 includes basic information 131, an evaluation distribution 132, and a posting acceptance area 133. The basic information 131 is basic information on restaurants. Specifically, the basic information 131 includes information on the number of reviews, five stars, reviews, addresses, telephones, and atmosphere.

  The word-of-mouth ranking is the ranking of restaurants counted from the number of reviews when each restaurant is arranged in descending order of the number of reviews. The five-star ranking is a ranking of restaurants counted from the one with the largest number of five stars when the restaurants are arranged in the order of the number of five stars.

  The word-of-mouth communication is information on the average value of restaurants evaluated in five stages by the word-of-mouth information contributor and the number of word-of-mouth information posted (number of word-of-mouth). The address and telephone are information on the restaurant address and telephone number. The atmosphere is information on the atmosphere of the restaurant most frequently registered by the poster.

  The evaluation distribution 132 is information on a five-level evaluation distribution made by a contributor to the word-of-mouth information for this restaurant.

  The posting reception area 133 is a reception area for receiving word-of-mouth information from the user. As word-of-mouth information, scoring (stars: 5, 4, 3, 2, 1), scene (dinner, lunch, etc.), amount per person (Less than 1,000 yen, 1,000-2,999 yen, 3,000-4,999 yen, 5,000-6,999 yen, 7,000-9,999 yen, 10,000 yen or more ), Store atmosphere (dates, entertainment, banquets, parties, joint parties, families, even one person, small groups), word of mouth, and word of mouth content.

  When the posting button 134 is clicked with a mouse or the like, the input information is transmitted to the information storage server 50, and the information storage server 50 stores the information.

  In addition, the user's nicknames (“Mr. XXXX” and “Mr. YYYY”) of the latest review information 122 and useful review information 123 on the review information output screen 120 shown in FIG. A hyperlink to the information is set.

  Then, when those nicknames are clicked with the mouse or the like in the user terminals 10a to 10c, the information provision processing unit 43 requests the information storage server 50 to transmit the information of the posting history of the poster, and has received the result. Posting history information is output to the user terminals 10a to 10c.

  FIG. 6 is a diagram showing an example of the contributor review post history output screen 140 output in this way. The contributor's word-of-mouth contribution log output screen 140 includes information on the number of word-of-mouth contributions, the number of support points, and the tendency of word-of-mouth.

  The number of review posts is information on the total number of review information posted by the contributor and the ranking of the contributors counted from the largest number of review posts when each contributor is arranged in descending order of the number of review posts. The support score is an index serving as a measure for measuring the degree of support of the poster by other users, and is a number obtained by subtracting the non-support number from the support number.

  Here, the number of support is the number that the reviewer's word-of-mouth information has been evaluated as useful by other users using the evaluation buttons 128a and 128c as shown in FIG. The number of disapprovals is the number that the reviewer's word-of-mouth information is evaluated as being useless by other users using the evaluation buttons 128b and 128d as shown in FIG.

  The word-of-mouth tendency includes evaluation distribution, budget, and genre information. The distribution of evaluation is information on the distribution of the evaluation of restaurants in five stages in the word-of-mouth information posted by the poster in the past. The budget is information on the distribution of restaurant budget amounts in the word-of-mouth information posted by the poster in the past. The genre is information on the distribution of genres of restaurants in the review information posted by the poster in the past.

  Further, when the display button 105 of the poster ranking display request reception area 103 is clicked with the mouse or the like on the top screen 100 shown in FIG. It requests to send information on contributor ranking.

  And the information provision process part 43 receives the information of the contributor ranking transmitted by the information storage server 50, and outputs the received information to the user terminals 10a to 10c. FIG. 7 is a diagram showing an example of the poster ranking output screen 150 output in this way. The contributor ranking output screen 150 includes information on rank, nickname, number of reviews posted, number of support points, and support rate.

  The ranking is the ranking when the posters are ranked in descending order of evaluation. Specifically, the ranking is made in descending order of the numerical value obtained by multiplying the number of contributions of the word of mouth information by the support rate. When these numbers are the same, a poster who has a large number of support points is regarded as a top poster. Further, when the support points are also the same, those contributors are assigned the same rank, and the contributors are displayed in alphabetical order using a contributor ID described later.

  In this example, the ranking is based on the number of reviews posted by the number of contributions multiplied by the support rate. However, the ranking of posters is ranked in descending order of the total number of reviews posted by the poster. Also good. Further, the ranking of the posters may be performed in descending order of the number of times the review information posted by the poster is viewed.

  The nickname is a nickname used when a poster posts word-of-mouth information. The number of reviews posted is the number of reviews posted by the poster in the past. The support score is an index serving as a measure for measuring the degree of support of the poster by other users, and is a number obtained by subtracting the non-support number from the support number. Like the support score, the support rate is an index that measures the degree to which each contributor is supported by other users, and the support number accounts for the total number of support and non-support. It is a ratio.

  In addition, in addition to the nickname of the poster, status icons 151a to 151d are output in the area for displaying the nickname. The status icons 151a to 151d are symbols (icons) expressed so that the evaluation content of the contributor of the word-of-mouth information can be understood at a glance.

  Specifically, the colors of the status icons 151a to 151d change depending on the support rate, and the numerical values shown in the status icons 151a to 151d change depending on the number of reviews posted. The color of the status icons 151a to 151d and the method of determining the numerical values shown in the status icons 151a to 151d will be described in detail later using FIG.

  In addition to numerical values, upward, horizontal, and downward arrows are displayed in the status icons 151a to 151d. The direction of this arrow indicates whether the current support rate has increased by more than a predetermined value (for example, 1% or more) compared to the support rate at a predetermined time in the past (for example, one week ago), or Indicates whether the increase or decrease in the support rate is within a predetermined range (for example, within a range of plus or minus 1%), or whether the current support rate has decreased by a predetermined value or more (for example, 1% or more) Yes.

  FIG. 8 is a diagram illustrating arrows indicating the change in the support rate of the status icons 160a to 160c.

  The status icon 160a is an example in which the current support rate has increased by a predetermined value or more compared to the support rate at a predetermined time in the past, and the arrow is pointing upward. The status icon 160b is an example in the case where the increase or decrease amount of the support rate at the present time from the support rate at a predetermined time in the past is within a predetermined range, and the arrow is horizontally oriented. The status icon 160c is an example of a case where the current support rate has dropped by a predetermined value or more compared to the support rate at a predetermined past time point, and the arrow is pointing downward.

  In addition, when the status icons 151a to 151d illustrated in FIG. 7 are clicked with a mouse or the like, the information provision processing unit 43 outputs the history information of the poster's support rate. Specifically, when the status icons 151a to 151d are clicked with a mouse or the like, the information provision processing unit 43 requests the information storage server 50 to transmit the history information of the poster support rate.

  And the information provision process part 43 receives the historical information transmitted by the information storage server 50, and outputs the received historical information to user terminal 10a-10c. FIG. 9 is a diagram illustrating an example of the support rate history output screen 160.

  As shown in FIG. 9, the information provision processing unit 43 outputs history information representing a temporal change in the poster's support rate in a graph with the support rate on the vertical axis and the time axis on the horizontal axis.

  In the case where the ranking of the contributors is performed in descending order of the total number of word-of-mouth information posted by the contributor, when the status icons 151a to 151d are clicked with a mouse or the like, the total number of word-of-mouth information is represented as a change over time. History information is output as a graph.

  In addition, when ranking the authors in the order of the number of times the review information posted by the contributor is viewed, when the status icons 151a to 151d are clicked with a mouse or the like, the number of times the contributor is viewed History information representing changes is output as a graph.

  Further, the information provision processing unit 43 displays the status icons 151a to 151d of a certain poster on the status icons 151a to 151d of other posters by operating the mouse or the like on the poster ranking output screen 150 shown in FIG. In addition, the word-of-mouth information of both contributors is output to the user terminals 10a to 10c when they are overlapped by a drag-and-drop operation.

  Specifically, when the two status icons 151a to 151d are overlapped by a drag-and-drop operation, the information providing processing unit 43 corresponds to the status icons 151a to 151d corresponding to the status icons 151a to 151d. It requests | requires to search whether there exists what was posted about the same restaurant among word-of-mouth information of a person's contributor.

  And the information provision process part 43 receives the information of the search result transmitted by the information storage server 50, and when there is the review information posted about the same restaurant, the review information for two persons is shown in FIG. Are output to the user terminals 10a to 10c in the format of the word-of-mouth information output screen 120 as shown in FIG.

  FIG. 10 is a diagram for explaining a drag-and-drop operation of the status icons 151a to 151d. As shown in FIG. 10, by dragging the status icon 151b of a certain contributor with the pointer 152 and dropping the status icon 151b on the status icon 151a with another contributor, the word-of-mouth information for two users is displayed. It is output to the terminals 10a to 10c.

  In addition, although it is supposed here that the word-of-mouth information posted about the same restaurant is output among the word-of-mouth information of two contributors corresponding to the status icons 151a to 151d overlapped by the drag and drop operation, the same It is good also as outputting the word-of-mouth information which satisfies other conditions, such as a genre.

  Returning to the description of FIG. 1, the control unit 44 is a control unit that totally controls the information providing server 40, and controls data exchange between the functional units.

  The information storage server 50 is a server that stores various information to be provided to the user. The information storage server 50 includes a communication processing unit 51, a storage unit 52, an information management unit 53, and a control unit 54.

  The communication processing unit 51 is a network interface that performs communication with the information providing server 40 or the information totaling server 60 via the network 70.

  The storage unit 52 is a storage device such as a hard disk device. The storage unit 52 stores store data 52a, contributor data 52b, post data 52c, specialty area store evaluation data 52d, store evaluation data 52e, contributor evaluation data 52f, support rate history data 52g, and contributor ranking data 52h. is doing.

  The store data 52a is basic data of each restaurant. FIG. 11 is a diagram illustrating an example of the store data 52a illustrated in FIG. As shown in FIG. 11, the store data 52a stores store ID, store name, genre, address, region, telephone number, transportation means, and coupon information. These are pieces of information received by an input device (not shown) of the information storage server 50 from an administrator of the information providing service.

  The store ID is an ID uniquely assigned to each restaurant. The store name is the name of each restaurant. The genre is a genre of food provided by each restaurant. The address is the address of each restaurant. The area is information on the area corresponding to the address. The telephone number is the telephone number of each restaurant.

  The transportation means is information on transportation means that is most convenient for going to each restaurant. The coupon is information on a coupon that can be used at each restaurant. When there is a coupon, the content is stored, and when there is no coupon, information “none” is stored.

  Returning to the description of FIG. 1, the contributor data 52b is basic data of the user who posted the word-of-mouth information. FIG. 12 is a diagram showing an example of the poster data 52b shown in FIG. As shown in FIG. 12, this contributor data 52b stores information on contributor ID, password, nickname, e-mail address, gender, date of birth, region, and genre. These pieces of information are information registered by operations of the user terminals 10a to 10c by the respective posters.

  The contributor ID is an ID uniquely assigned to each contributor. The password is a password that is input when each contributor posts. The nickname is a nickname used by each poster for posting. The e-mail address is the e-mail address of each contributor. The gender is the gender of each contributor. The date of birth is the date of birth of each contributor.

  The region is information on a region that each poster is good at evaluating restaurants. In the example of FIG. 12, only one piece of region information is registered for each contributor, but a plurality of regions may be registered.

  The genre is genre information that each poster is good at evaluating restaurants. In the example of FIG. 12, only one genre information is registered for each contributor, but the contributor may register a plurality of genres.

  Returning to the description of FIG. 1, the post data 52c is data in which word-of-mouth information posted by a contributor on the post acceptance screen 130 as shown in FIG. 5 is stored. FIG. 13 is a diagram showing an example of post data 52c shown in FIG.

  As shown in FIG. 13, this posting data 52c includes a posting ID, a contributor ID, a posting date, a store ID, a star rating, a scene, an amount of money, an atmosphere, a word of mouth, a word of mouth, a support rate, a non-support rate, and the number of views. The information is memorized.

  The posting ID is an ID assigned to each piece of review information posted by the poster. The contributor ID is an ID assigned to the contributor who posted the word-of-mouth information. This poster ID corresponds to the poster ID shown in FIG. The posting date and time is the date and time when each review information is posted.

  The store ID is an ID uniquely assigned to each restaurant. This store ID corresponds to the store ID shown in FIG. The star rating is a restaurant rating made by the contributor. This rating is made in five stages, with five stars being the highest rating and one star being the lowest rating.

  The scene is a restaurant scene evaluated by the poster. Specifically, the scene is selected by the contributor from “dinner”, “lunch”, “others”, and the like. The amount is information on the budget amount of the restaurant registered by the contributor. The atmosphere is information on the atmosphere of the restaurant registered by the poster.

  The review title is the title of the review information registered by the contributor. The word of mouth content is the content of the word of mouth information registered by the contributor. The number of support is the number of users who have supported (determined to be useful) the review information posted by the poster. The number of disapprovals is the number of users who did not support the word-of-mouth information posted by the contributor (determined not useful).

  The information management unit 53 receives the information from the information providing server 40 each time the evaluation buttons 128a to 128d are clicked with a mouse or the like on the word-of-mouth information output screen 120 shown in FIG. Update rate information.

  The number of browsing is information on the number of times each review information is browsed by the user. The information management unit 53 updates the information on the number of views each time the word-of-mouth information is transmitted to the information providing server 40 for output to the user terminals 10a to 10c.

  Returning to the description of FIG. 1, the specialty area store evaluation data 52d is data in which information on evaluation of each restaurant made by the poster is stored. FIG. 14 is a diagram showing an example of the specialty area store evaluation data 52d shown in FIG.

  Here, this specialty area store evaluation data 52d is for each restaurant corresponding to each contributor's area registered in the poster data 52b among all the word-of-mouth information registered in the posting data 52c. The evaluation of restaurants included in the word-of-mouth information posted by the contributor is tabulated for each restaurant.

  As shown in FIG. 14, this specialty area store evaluation data 52d includes number, store ID, average rating, number of reviews, number of reviews, star rating, five star rating, budget, atmosphere, gender / generation, latest Each information of word-of-mouth information and useful word-of-mouth information is stored.

  The number is a serial number of each restaurant. The total number of restaurants registered in the specialty area evaluation data 52d can be known from this number. The store ID is an ID uniquely assigned to each restaurant. This store ID corresponds to the store ID shown in FIG. The evaluation average score is an average value of star evaluations calculated by calculating the star evaluations of the posted data 52c shown in FIG. 13 for each restaurant.

  The number of word-of-mouth communication is the total number of word-of-mouth information for each restaurant, where the number of word-of-mouth information in post data 52c shown in FIG. The word-of-mouth ranking is the ranking of restaurants counted from the number of reviews when each restaurant is arranged in descending order of the number of reviews.

  The star rating is information obtained by tabulating the star rating of the posted data 52c shown in FIG. 13 for each restaurant. The five-star ranking is a ranking of restaurants counted from the one with the largest number of five stars when the restaurants are arranged in the order of the number of five stars. The budget is information obtained by tabulating the amount of post data 52c shown in FIG. 13 for each restaurant.

  The atmosphere is information obtained by tabulating the atmosphere of the posting data 52c shown in FIG. 13 for each restaurant. The sex / generation is information obtained by tabulating the sex / generation of the poster specified by the poster ID of the posting data 52c shown in FIG. 13 for each restaurant. The gender / generation of each contributor is determined by examining the sex and date of birth from the contributor data 52b using the contributor ID.

  The latest review information is information for specifying the latest review information among the review information posted to each restaurant, and the post ID of the post data 52c shown in FIG. 13 corresponding to the latest review information is registered. It has been done.

  The useful word-of-mouth information is information for identifying word-of-mouth information determined to be useful by the user among the word-of-mouth information posted to each restaurant, and is shown in FIG. 13 corresponding to the word-of-mouth information determined to be useful. The posting ID of the posting data 52c is registered. Specifically, the useful word-of-mouth information is a post ID for identifying the selected word-of-mouth information when a predetermined number of word-of-mouth information having a high number of support points obtained by subtracting the number of unsupported items from the number of support items is selected.

  In addition, here, it is supposed that each contributor will summarize the word-of-mouth information posted about the area where he is good, but the word-of-mouth information posted by each contributor about the cuisine genre of the restaurant he is good at It is good also as creating the evaluation data of a restaurant.

  Returning to the description of FIG. 1, the store evaluation data 52e is a total of evaluations of restaurants included in all the word-of-mouth information registered in the post data 52c. This store evaluation data 52e is similar to the specialty area store evaluation data 52d shown in FIG. 14, and includes a number, a store ID, an evaluation average score, the number of reviews, the number of reviews, a star rating, a five star rank, a budget, and an atmosphere. , Gender / generation, latest word of mouth information, useful word of mouth information. However, this information differs from the specialty area store evaluation data 52d in that the information is a total result of restaurant evaluations included in all the word-of-mouth information registered in the posted data 52c.

  This store evaluation data 52e is calculated by summing up all the word-of-mouth information instead of outputting the restaurant ranking generated based on the word-of-mouth information posted by each contributor on the area he / she is good at as shown in FIG. When the information providing server 40 receives the restaurant ranking output request generated in this way from the user terminals 10a to 10c, it is used to output such a restaurant ranking.

  The contributor evaluation data 52f is data that stores information on the contributor's evaluation made by another user to the contributor who posted the word-of-mouth information. FIG. 15 is a diagram showing an example of the poster evaluation data 52f shown in FIG.

  As shown in FIG. 15, this contributor evaluation data 52f includes a number, a contributor ID, the number of reviews posted, the number of reviews posted, a star rating, a budget, a genre, a support count, a non-support count, a support score, a support rate, Stores information on the number of icons and word-of-mouth information viewed.

  The number is a serial number of each contributor. By this number, the total number of posters registered in the poster evaluation data 52f can be known. The contributor ID is an ID uniquely assigned to each contributor. This poster ID corresponds to the poster ID shown in FIG.

  The number of reviews posted is the total number of reviews posted by each poster. The word-of-mouth contribution ranking is the ranking of the number of contributors counted in descending order of the number of word-of-mouth contributions when the number of word-of-mouth contributions is arranged in descending order.

  The star rating is information obtained by tabulating the five-level ratings of restaurants evaluated by each poster. Specifically, this is information obtained by counting how many times the poster has evaluated each star. The budget is information obtained by tabulating the number of word-of-mouth information posted by each contributor for each amount. The genre is information obtained by tabulating the number of word-of-mouth information posted by each contributor for each genre of restaurants.

  The number of support is the total number of users who supported (determined to be useful) the word-of-mouth information posted by each contributor. The number of disapprovals is the total number of users who did not support the word-of-mouth information posted by each contributor (determined to be useless). The number of support points is an index that serves as a standard for measuring the degree to which each contributor is supported by other users, and is a number obtained by subtracting the number of non-supports from the number of support.

  Like the support score, the support rate is an index that measures the degree to which each contributor is supported by other users, and the support number accounts for the total number of support and non-support. It is a ratio.

  The icons are information indicating the types of status icons 151a to 151d output in association with each poster when the poster ranking output screen 150 as shown in FIG. 7 is output to the user terminals 10a to 10c. .

  The status icons 151a to 151d are configured so that the number of word-of-mouth contributions, the number of support points, and the change in the support rate can be seen at a glance. The method for determining the icon type will be described in detail when the information totaling server 60 is described.

  The number of word-of-mouth information browsing is information on the number of times word-of-mouth information posted by each contributor has been viewed by the user.

  Returning to the description of FIG. 1, the support rate history data 52 g is data that stores information on temporal changes in the support rate of each contributor. FIG. 16 is a diagram illustrating an example of the support history data 52g illustrated in FIG. The support rate history data 52g stores support rate data in association with a poster ID and a predetermined time in the past.

  The contributor ID is an ID uniquely assigned to each contributor. This poster ID corresponds to the poster ID of the poster data 52b shown in FIG. The support rate is the ratio of the support number to the total number of the total number of support and non-support. This support rate is a value in the past predetermined time of the support rate of the contributor evaluation data 52f shown in FIG.

  In the example of FIG. 16, the predetermined time in the past is set by dividing every week such as “one week ago”, “two weeks ago”, “three weeks ago”,. However, the present invention is not limited to this, and may be divided at an arbitrary time.

  Returning to the description of FIG. 1, the contributor ranking data 52h is ranking data in which the contributors are arranged in descending order of (number of reviews posted × supported points). The poster ranking output screen 150 shown in FIG. 7 is output based on the poster ranking data 52h.

  FIG. 17 is a diagram illustrating an example of the poster ranking data 52h illustrated in FIG. The contributor ranking data 52h stores information on rank, contributor ID, nickname, icon, number of reviews posted, number of support points, and support rate.

  The ranking is the ranking of the contributors counted in descending order of (number of reviews posted × number of supporting points) when the posters are arranged in order of increasing (number of reviews posted × number of supporting points). The contributor ID is an ID uniquely assigned to each contributor. This poster ID corresponds to the poster ID shown in FIG.

  The nickname is a nickname used by each poster for posting. This nickname corresponds to the nickname of the poster data 52b shown in FIG. The icons are information of the types of status icons 151a to 151d that are output in association with each poster and are output so that the number of word-of-mouth contributions, the number of support points, and the support rate can be understood at a glance. This icon corresponds to the icon of the contributor evaluation data 52f shown in FIG.

  The number of reviews posted is the total number of reviews posted by each poster. The number of reviews posted corresponds to the number of reviews posted in the contributor evaluation data 52f shown in FIG. The support score is an index that serves as a measure for measuring the degree to which each contributor is supported by other users. This support score corresponds to the support score of the contributor evaluation data 52f shown in FIG.

  The support rate is an index serving as a standard for measuring the degree to which each contributor is supported by other users, like the support score, and corresponds to the support rate of the contributor evaluation data 52f shown in FIG. .

  Returning to the description of FIG. 1, the information management unit 53 sends a data transmission request or search request stored in the storage unit 52 from the information providing server 40 or the information totaling server 60, and stores data in the storage unit 52. The management unit manages information by executing a requested process when a write request, an update request for data stored in the storage unit 52, or the like is received.

  The control unit 53 is a control unit that controls the information storage server 50 as a whole, and controls data exchange between the functional units.

  The information totaling server 60 is a server that counts the word-of-mouth information of restaurants posted by contributors and the evaluation information of contributors evaluated by other users with respect to the word-of-mouth information posted by contributors. The information totaling server 60 includes a communication processing unit 61, a storage unit 62, a store evaluation information totaling unit 63, and a contributor evaluation information totaling unit 64.

  The communication processing unit 61 is a network interface that performs communication with the information providing server 40 and the information storage server 50 via the network 70.

  The storage unit 62 is a storage device such as a hard disk device. The storage unit 62 stores icon determination data 62a. The icon determination data 62a is a determination for determining the type of status icons 151a to 151d output in association with each poster when the poster ranking output screen 150 shown in FIG. 7 is output to the user terminals 10a to 10c. It is data that stores the reference.

  FIG. 18 is a diagram illustrating an example of the icon determination data 62a illustrated in FIG. The icon determination data 62a stores information on the types of status icons 151a to 151d in association with the support rate and the number of reviews posted.

  The support rate is the ratio of the support number to the total number of the total number of support and non-support. The number of reviews posted is the total number of reviews posted by each poster. For example, when the support rate is 67% and the number of reviews posted is 52, the types of status icons 151a to 151d are “blue 100”.

  In the example of FIG. 18, the difference in the support rate is expressed by the difference in the colors of the status icons 151a to 151d, and the difference in the number of word-of-mouth contributions is expressed by a number. However, this expression method is not limited to this, and the difference in the support rate is expressed by a difference in the numbers, and the difference in the number of reviews posted may be expressed by the colors of the status icons 151a to 151d. .

  Moreover, it is good also as expressing the difference, such as a support rate and the number of word-of-mouth contributions, in the form of status icons 151a-151d. Furthermore, the evaluation of the contributor expressed using the status icons 151a to 151d is not limited to the support rate and the number of word-of-mouth contributions, and may be other things such as the number of support points.

  Returning to the description of FIG. 1, the store evaluation information totaling unit 63 is a totaling unit that periodically totals word-of-mouth information on restaurants posted by contributors.

  Specifically, the store evaluation information totaling unit 63 acquires the post data 52c shown in FIG. 13 from the information storage server 50, and stores the specialty area store evaluation data 52d shown in FIG. The evaluation data 52e generates the evaluation average score, the number of reviews, the number of reviews, the star rating, the five star ranking, the budget, the atmosphere, the gender / generation, the latest review information, and the useful word of mouth information, and the information storage server 50 The process to memorize such information is performed.

  The contributor evaluation information totaling unit 64 is a totalizing unit that totals the evaluation information of contributors evaluated by other users with respect to the word-of-mouth information posted by contributors.

  Specifically, the poster evaluation information totaling unit 64 acquires the posting data 52c shown in FIG. 13 from the information storage server 50, and the number of reviews posted by the poster evaluation data 52f shown in FIG. The number of reviews posted, ranking, star rating, budget, genre, number of supports, number of unsupported, number of support points, support rate, icon information are generated, and the information storage server 50 stores the information.

  When generating icon information, the contributor evaluation information totaling unit 64 generates icon information based on the determination criteria stored in the icon determination data 62a. At that time, the poster evaluation information totaling unit 64 acquires the support rate history data 52g from the information storage server 50, and compares the current support rate value with the past support rate value, thereby the status icons 151a to 151a. In 151d, the direction of the arrow indicating the change in the support rate is determined.

  Further, when the information storage server 50 stores new support rate information, the contributor evaluation information totaling unit 64 stores the old support rate value as the support rate history data 52g shown in FIG. Furthermore, the contributor evaluation information totaling unit 64 arranges the contributors registered in the contributor evaluation data 52f in the descending order of the number of reviews posted (supported points × the number of support points), whereby the contributor ranking data 52h shown in FIG. It is generated and stored in the information storage server 50.

  The control unit 65 is a control unit that controls the information totaling server 60 as a whole, and controls data exchange between the functional units.

  Next, a processing procedure of word-of-mouth information aggregation processing according to the present embodiment will be described. FIG. 19 is a flowchart illustrating the processing procedure of the word-of-mouth information aggregation processing according to the present embodiment. As shown in FIG. 19, first, the store evaluation information totaling unit 63 of the information totaling server 60 performs time information acquisition processing for periodically acquiring time information from a clock (not shown) provided in the information totaling server 60. Perform (step S101).

  Then, the store evaluation information totaling unit 63 checks whether or not the current time is a preset time (step S102). If the current time is not a preset time (No at Step S102), the store evaluation information totaling unit 63 returns to Step S101 and continues the time information acquisition process.

  If the current time is a preset time (step S102, Yes), the store evaluation information totaling unit 63 sends the store data 52a, the poster data 52b, the posted data 52c, and the support rate history from the information storage server 50. A data reading process for reading the data 52g is performed (step S103).

  Thereafter, the store evaluation information totaling unit 63 totals restaurant evaluation information for each store based on the posted data 52c, and performs store evaluation information totaling processing for requesting that the totaled evaluation information be stored in the information storage server 50. (Step S104). The information management unit 52 of the information storage server 50 that has received this request stores the received evaluation information in the storage unit 52 as the specialty area store evaluation data 52d and the store evaluation data 52e.

  Subsequently, the contributor evaluation information totaling unit 64 totals the contributor evaluation information for each contributor based on the post data 52c, and requests the contributor evaluation information to store the totaled evaluation information in the information storage server 50. Aggregation processing is performed (step S105). The information management unit 52 of the information storage server 50 that has received this request stores the received evaluation information in the storage unit 52 as the poster evaluation data 52f, the support history data 52g, and the poster ranking data 52h.

  Then, the store evaluation information totaling unit 63 checks whether or not this word-of-mouth information totaling process end request has been received by an input device (not shown) of the information totaling server 60 (step S106), and the word-of-mouth information totaling process end request Is received (step S106, Yes), the word-of-mouth information aggregation process is terminated. When the termination request for the word-of-mouth information totaling process has not been received (step S106, No), the process returns to step S101 and the time information acquisition process is performed again.

  Next, the processing procedure of the store evaluation information tabulation process shown in FIG. 19 will be described in more detail. FIG. 20 is a diagram for explaining the processing procedure of the store evaluation information tabulation process shown in FIG. Here, the case where the store evaluation information registered in the specialty area store evaluation data 52d shown in FIG. 14 is totaled will be described.

  As illustrated in FIG. 20, first, the store evaluation information totaling unit 63 selects a restaurant corresponding to the poster's area registered in the poster data 52b from the word-of-mouth information stored in the posted data 52c. The posted word-of-mouth information is extracted (step S201). The area and genre of each restaurant can be examined with reference to the store data 52a.

  And the shop evaluation information total part 63 totals the number of extracted word-of-mouth information for every restaurant, and calculates the number of word-of-mouth in the specialty area shop evaluation data 52d (step S202). Subsequently, the store evaluation information totaling unit 63 ranks the restaurants in descending order of the number of reviews posted, and calculates the number of reviews in the specialty area store evaluation data 52d (step S203).

  Thereafter, the store evaluation information totaling unit 63 totals the star ratings of the extracted word-of-mouth information for each restaurant, and calculates the star rating in the specialty area store evaluation data 52d (step S204). Then, the store evaluation information totaling unit 63 ranks the restaurants in order of increasing five stars in the star evaluation totaled for each restaurant, and calculates the five-star rank in the specialty area store evaluation data 52d (step). S205).

  Thereafter, the store evaluation information totaling unit 63 calculates an evaluation average score in the specialty area store evaluation data 52d using the information of star evaluation totaled for each restaurant (step S206). Then, the store evaluation information totaling unit 63 totals the information on the amount of money in the extracted word-of-mouth information for each restaurant, and generates budget information in the specialty area store evaluation data 52d (step S207).

  Subsequently, the store evaluation information totaling unit 63 totals the atmosphere information in the extracted word-of-mouth information for each restaurant, and generates the atmosphere information in the specialty area store evaluation data 52d (step S208).

  Then, the store evaluation information totaling unit 63, based on the poster ID in the extracted word-of-mouth information and the gender and date of birth information corresponding to the poster ID stored in the poster data 52b. The gender / generation information is aggregated for each restaurant, and the gender / generation information in the specialty area evaluation data 52d is generated (step S209).

  Subsequently, the store evaluation information totaling unit 63 determines the latest word-of-mouth information in the evaluation data 52d from the posting date / time information in the extracted word-of-mouth information (step S210). Further, the store evaluation information totaling unit 63 determines useful word-of-mouth information in the evaluation data 52d by calculating the number of support points from the support rate and non-support rate information in the extracted word-of-mouth information (step S211).

  Thereafter, the store evaluation information totaling unit 63 transmits the result obtained by the processing from step S201 to step S211 to the information storage server 50 (step S212), and the result is sent to the information storage server 50 as the specialty area store evaluation data. 52d is stored, and this store evaluation information totaling process is terminated.

  Here, the case where the store evaluation information registered in the specialty area store evaluation data 52d shown in FIG. 14 is totaled has been described. However, when the store evaluation information registered in the store evaluation data 52d is totalized, In step S201, instead of extracting the word-of-mouth information posted to the restaurant corresponding to the poster's area registered in the poster data 52b, all the word-of-mouth information is acquired, and in the subsequent processing, Each process is performed on all acquired word-of-mouth information.

  Next, the processing procedure of the contributor evaluation information tabulation process shown in FIG. 19 will be described in more detail. FIG. 21 is a diagram for describing the processing procedure of the contributor evaluation information aggregation processing shown in FIG. As shown in FIG. 21, first, the contributor evaluation information totaling unit 64 sums up the number of reviews posted in the posting data 52c for each contributor, and calculates the number of reviews posted in the contributor evaluation data 52f (step). S301).

  Then, the contributor evaluation information totaling unit 64 ranks contributors in descending order of the number of reviews posted for each contributor, and calculates the number of reviews posted in the contributor evaluation data 52f (step S302).

  Subsequently, the poster evaluation information totaling unit 64 totals the star ratings stored in the posting data 52c for each poster, and calculates the star rating in the poster evaluation data 52f (step S303). Then, the poster evaluation information totaling unit 64 totals the amount information stored in the posting data 52c for each poster, and generates budget information in the poster evaluation data 52f (step S304).

  Thereafter, the poster evaluation information totaling unit 64 obtains the genre information of the restaurant based on the store ID stored in the post data 52c and the genre information corresponding to the store ID stored in the store data 52a. The information is totaled for each contributor, and genre information in the contributor evaluation data 52f is generated (step S305).

  Then, the poster evaluation information totaling unit 64 totals the information on the number of support and the number of disapproval stored in the post data 52c for each contributor, and calculates the number of support and the number of unsupport in the poster evaluation data 52f ( Step S306).

  Subsequently, the contributor evaluation information totaling unit 64 calculates the support score in the contributor evaluation data 52f by subtracting the unsupported number from the total supported number (step S307). Then, the contributor evaluation information totaling unit 64 calculates a support rate in the contributor evaluation data 52f by calculating a ratio of the support number in the total number of the support number and the non-support number (step). S308).

  Thereafter, the poster evaluation information totaling unit 64 refers to the icon determination data 62a and the support rate history data 52g, and counts the number of reviews posted for each contributor specified by the contributor ID, and the calculated support rate. Based on the past support rate, icon information in the poster evaluation data 52f is generated (step S309).

  Subsequently, the contributor evaluation information totaling unit 64 sums up the number of views of the posting data 52c for each contributor, and calculates the number of reviews of word-of-mouth information in the contributor evaluation data 52f (step S310).

  Then, the contributor evaluation information totaling unit 64 includes information on the nickname stored in the contributor data 52b, icons of each contributor generated for the contributor evaluation data 52f, the number of reviews posted, the number of support points, and the support rate information. Using the above, the poster ranking data 52h is generated by arranging the posters in the descending order of (number of reviews posted × number of support points) (step S311).

  Here, when (the number of reviews contributed × the number of support points) is the same, a contributor with a large number of support points is regarded as an upper contributor. Further, if the support points are also the same, those posters are assigned the same ranking, and ranking is performed in alphabetical order using the poster ID.

  Thereafter, the poster evaluation information totaling unit 64 transmits the result obtained by the processing from step S301 to step S311 to the information storage server 50 (step S312), and the result is sent to the information storage server 50 by the poster evaluation data. 52f is stored as contributor ranking data 52h, and the contributor evaluation information totaling process is terminated.

  Below, the process sequence of the restaurant information provision process which concerns on a present Example is demonstrated. FIG. 22 is a flowchart illustrating the processing procedure of the restaurant information providing process according to the present embodiment.

  As shown in FIG. 22, first, the information provision processing unit 43 of the information provision server 40 accepts a processing request for restaurant information provision processing from the user terminals 10a to 10c (step S401), and examines the contents of the accepted processing request. (Step S402).

  If the received processing request is a review information posting process execution request, the information provision processing unit 43 and the information management unit 53 of the information storage server 50 execute a review information posting process (step S403).

  Specifically, the information provision processing unit 43 outputs a post acceptance screen 130 as shown in FIG. 5 to the user terminals 10a to 10c, and accepts input of word-of-mouth information by the user. Then, the information provision processing unit 43 transmits the received word-of-mouth information to the information management unit 53. Then, the information management unit 53 stores the received word-of-mouth information in the storage unit 52 as post data 52c.

  After completion of the word-of-mouth information posting process, the information provision processing unit 43 checks whether or not this restaurant information provision process termination request has been received by an input device (not shown) of the information provision server 40 (step S408). When the end request for the store information providing process is received (step S408, Yes), the restaurant information providing process is ended.

  When the termination request for the restaurant information provision process has not been received (No at Step S408), the process returns to Step S401, and the process for accepting the processing request for the restaurant information provision process from the user terminals 10a to 10c is performed again.

  When the content of the processing request checked in step S402 is a restaurant search processing execution request made by the user on the top screen 100 described in FIG. 2, the information provision processing unit 43 and the information management unit 53 Store search processing is executed (step S404).

  Specifically, the information provision processing unit 43 transmits the narrowing-down conditions input on the top screen 100 to the information management unit 53 and requests to search for restaurant information that matches the narrowing-down conditions such as the designation of the area.

  The information management unit 53 that has received this request searches the restaurant data 52a and the specialty area store evaluation data 52d for restaurant information and evaluation information for the restaurant that match the narrowing-down conditions, and the searched information is the information provision processing unit 43. Send to.

  Thereafter, the information provision processing unit 43 receives the information transmitted by the information management unit 53, generates data constituting the regional store ranking output screen 110 as shown in FIG. 3 using the information, Data is transmitted to the user terminals 10a to 10c, and the regional store ranking output screen 110 is output. After the restaurant search process ends, the process proceeds to step S408, and the subsequent processes are executed.

  In addition, instead of outputting the restaurant ranking generated based on the word-of-mouth information posted by each contributor on the area he / she is good at, information on the restaurant ranking output request generated by summing up all the word-of-mouth information When the provision processing unit 43 receives from the user terminals 10a to 10c, the information provision processing unit 43 configures the regional store ranking output screen using the store evaluation data 52e generated by collecting all the word-of-mouth information. The data to be generated is generated, and the data is transmitted to the user terminals 10a to 10c to output the regional store ranking output screen.

  The content of the processing request checked in step S402 was a word-of-mouth information output request made by clicking the store name [genre] with the mouse or the like in the restaurant ranking 111 on the regional ranking output screen 110 shown in FIG. In this case, the information provision processing unit 43 and the information management unit 53 execute a word-of-mouth information output process (step S405).

  Specifically, the information provision processing unit 43 transmits information on a restaurant clicked with a mouse or the like to the information management unit 53 and requests to search for word-of-mouth information corresponding to the restaurant. Upon receiving this request, the information management unit 53 searches the post data 52c for the latest review information and useful review information of the specialty area store evaluation data 52d, and sends the searched review information to the information provision processing unit 43. Send.

  Thereafter, the information provision processing unit 43 receives the information transmitted by the information management unit 53, generates data constituting the word-of-mouth information output screen 120 as shown in FIG. 4 using the information, and stores the data. It transmits to the user terminals 10a-10c, and the word-of-mouth information output screen 120 is output. After the word-of-mouth information output process ends, the process proceeds to step S408, and the subsequent processes are executed.

  When the content of the processing request checked in step S402 is a contributor ranking output request made by the user on the top screen 100 described in FIG. 2, the information provision processing unit 43 and the information management unit 53 Ranking output processing is executed (step S406).

  Specifically, when the display button 105 of the contributor ranking display reception area 103 on the top screen 100 is clicked by an operation of a mouse or the like, the information provision processing unit 43 displays the contributor ranking to the information management unit 53. Request to send information.

  The information management unit 53 that has received this request transmits the information stored as the poster ranking data 52 h to the information provision processing unit 43. Thereafter, the information provision processing unit 43 receives the information transmitted by the information provision processing unit 43, generates data constituting the poster ranking output screen 150 as shown in FIG. 7 using the information, Data is transmitted to the user terminals 10a to 10c and the poster ranking output screen 150 is output.

  Further, when the status icons 151a to 151d on the poster ranking output screen 150 are clicked by the user with the mouse or the like, the information provision processing unit 43 displays the information of the poster corresponding to the clicked status icons 151a to 151d. The information management unit 53 is requested to transmit the support history information.

  Upon receiving this request, the information management unit 53 reads the support rate history information of the poster corresponding to the clicked status icons 151 a to 151 d from the support rate history data 52 g and transmits it to the information provision processing unit 43.

  Thereafter, the information provision processing unit 43 receives the information transmitted by the information provision processing unit 43, generates data constituting the support rate history output screen 160 as shown in FIG. 9 using the information, Data is transmitted to the user terminals 10a to 10c and the support rate history output screen 160 is output.

  Further, as described with reference to FIG. 10, drag and drop for dragging the status icons 151 a to 151 d of a certain poster and dropping them on the status icons 151 a to 151 d of other posters is performed on the poster ranking output screen 150. When the operation is performed with a mouse or the like, the information provision processing unit 43 requests the information management unit 53 to search for word-of-mouth information posted by both posters on the same restaurant.

  The information management unit 53 that has received this request searches the posted data 52c for the review information posted by both contributors on the same restaurant, and transmits the review information obtained by the search to the information provision processing unit 43. In addition, the restaurant information and the evaluation information for the restaurant are searched from the store data 52a and the specialty area store evaluation data 52d, and the searched information is transmitted to the information provision processing unit 43.

  Thereafter, the information provision processing unit 43 receives the information transmitted by the information provision processing unit 43, and displays the latest word of mouth information 122 and the useful word of mouth information 123 for two persons on the word of mouth information output screen 120 as shown in FIG. The data constituting the word-of-mouth information output screen replaced with the word-of-mouth information is generated, and the data is transmitted to the user terminals 10a to 10c to output the word-of-mouth information output screen.

  When such processing is completed, the process proceeds to step S408, and the subsequent processing is executed.

  The content of the processing request checked in step S402 is the latest review information 122 on the review information output screen 120 shown in FIG. 4, the nickname of the contributor in the useful review information 123, or the contributor ranking output screen 150 shown in FIG. If the poster information output request is made by clicking on the nickname of the poster in the mouse or the like, the information provision processing unit 43 and the information management unit 53 execute a poster information output process (step S407). ).

  Specifically, the information provision processing unit 43 requests the information management unit 53 to transmit the posting history information of the poster corresponding to the poster whose nickname is clicked. The information management unit 53 that has received this request reads out the posting history information of the poster corresponding to the poster whose nickname was clicked from the poster evaluation data 52 f and transmits it to the information provision processing unit 43.

  Thereafter, the information provision processing unit 43 receives the information transmitted by the information management unit 53, generates data constituting the poster review history output screen 140 as shown in FIG. Data is transmitted to the user terminals 10a to 10c, and the contributor's word-of-mouth history output screen 140 is output.

  After the end of the poster information output process, the process proceeds to step S408, and the subsequent processes are executed.

  In the above embodiment, the case where the evaluation information management process is realized on each computer has been described. However, the program for realizing the evaluation information management process is recorded on a computer-readable recording medium, and this recording medium is recorded. The evaluation information management processing may be realized by causing the computer to read and execute the program recorded in the above.

  FIG. 23 is a block diagram illustrating a hardware configuration of the computer 200 that realizes the evaluation information management process. As shown in FIG. 23, the computer 200 includes a CPU 210 that executes the program, an input device 220 that inputs data, a ROM 230 that stores various data, a RAM 240 that stores calculation parameters and the like, and an evaluation information management process A reading device 250 that reads a program from a recording medium 300 that records a program for realizing the above, an output device 260 such as a display, and a network interface 270 that exchanges data with other computers via the network 400 However, they are connected by a bus 280.

  The CPU 210 implements the evaluation information management process by reading the program recorded on the recording medium 300 via the reading device 250 and then executing the program. Examples of the recording medium 300 include an optical disk, a flexible disk, a CD-ROM, and a hard disk. Further, this program may be installed in the computer 200 via the network 400.

  As described above, in this embodiment, the information storage server 50 stores the evaluation information indicating the evaluation of the poster in association with each poster, and the information providing server 40 is stored in the information storage server 50. Since the status icons 151a to 151d indicating the poster's evaluation based on the evaluation information are output together with the identification information (nickname) for identifying the poster, by using the status icons 151a to 151d, even the poster's Even if the number increases, the user can easily check the poster's evaluation without deteriorating the operability, and the viewability can be improved.

  In this embodiment, the evaluation information includes the history information of the poster's evaluation, and the status icons 151a to 151d are diagrams representing the history information of the poster's evaluation (in the status icons 151a to 151d shown in FIG. 7). Arrow) is included inside, so even if the number of contributors increases, the user can easily check the reviewer's evaluation history information without degrading operability. Can be improved.

  Further, in the present embodiment, when the information providing server 40 clicks the status icons 151a to 151d with a mouse or the like, the history information of the poster's evaluation corresponding to the clicked icon (support rate shown in FIG. 9). Since the history output screen 160) is output, it is possible to efficiently provide such information to a user who desires to browse the detailed information of the poster's evaluation.

  Further, in this embodiment, when the status icon 151a to 151d of a certain contributor is superimposed on the status icons 151a to 151d of other contributors by a drag and drop operation, the information storage server 50 Since word-of-mouth information for a common restaurant is extracted from the word-of-mouth information posted by each poster corresponding to the icon, and the information providing server 40 outputs the word-of-mouth information extracted by the information storage server 50. Among information posted by a plurality of contributors, such information can be efficiently provided to users who wish to view word-of-mouth information for a common restaurant.

  Further, in this embodiment, the evaluation of the contributor is indicated, and the evaluation information output by the status icons 151a to 151d is the number of the word-of-mouth information posted by the contributor and / or the word-of-mouth information posted by the contributor. If the user wishes to view such information, even if the number of contributors increases, the operability is deteriorated. Therefore, the user can easily check the poster's evaluation, and the viewability can be improved.

(Other examples)
Although the embodiments of the present invention have been described so far, the present invention may be implemented in various different embodiments in addition to the above-described embodiments within the scope of the technical idea described in the claims. It ’s good.

  For example, when the hyperlink of the store name [genre] shown in FIG. 3 is clicked with a mouse or the like, a word-of-mouth information output screen 170 as shown in FIG. 24 may be displayed. 24, the same parts as those in FIG. 4 are denoted by the same reference numerals. This word-of-mouth information output screen 170 includes basic information 121, high-level word-of-mouth information 171, and level order word-of-mouth information 172.

  The high-level word-of-mouth information 171 is word-of-mouth information only for contributors with a high level determined by user support. That is, the high-level word-of-mouth information 171 is displayed only when a user whose level is a predetermined value or higher posts word-of-mouth information for the restaurant indicated by the basic information 121. The user level will be described later in detail.

  The level order word-of-mouth information 172 is the word-of-mouth information posted by the contributor, but unlike the latest word-of-mouth information 122 and the useful word-of-mouth information 123 shown in FIG. 4, the word-of-mouth information is displayed in descending order of the contributor level. The level order word-of-mouth information 172 displays the word-of-mouth information with the background color changed according to the level of the poster. Therefore, the user browsing the word-of-mouth information output screen 170 can confirm the level of the contributor who posted the word-of-mouth information at a glance, and as a result, word-of-mouth information with high credibility can be easily selected. Note that the change in the background color according to the level of the poster is not applied only to the level order word-of-mouth information 172, but the background color according to the level of the poster is added to the latest word-of-mouth information 122 shown in FIG. May be applied. Further, it is not only the background color that identifies the poster's level, but it may be, for example, the font color or the shape or color of the frame of word of mouth information.

  The level icons 173a to 173c are icons indicating the level of the poster who posted each word of mouth information. Here, for users who can post word-of-mouth information, levels corresponding to the number of logins and support points are calculated by the contributor evaluation information totaling unit 64 of the information totaling server 60. That is, as the number of times each user accesses and logs in to the information providing server 40 increases, for example, the level increases as the number of points owned by the user increases. In this way, by increasing the level according to the number of logins by the user, it is possible to motivate the user to log in frequently at least. In addition, a certain level can be given to a user who does not post word-of-mouth information but only browses. In addition, the level of each user increases as the support from other users for word-of-mouth information increases.

  In addition, as the support points used for calculating the level, the support points in the above-described embodiment can be used, but the support points can be obtained after weighting the evaluation according to the level of the user who evaluates the posting. . In other words, posts that were supported by users with higher levels had higher support points than posts that were supported by users with lower levels, and posts that were not supported by users with higher levels were not supported by users with lower levels. Support points should be lower than posts.

  Thus, by calculating the level for each user and storing it in the storage unit 52 of the information storage server 50, it is possible to evaluate the contribution of the word of mouth information in consideration of the level of the evaluator. It is possible to provide word-of-mouth information posted by high-value contributors and word-of-mouth information evaluated by high-level evaluators as word-of-mouth information with high credibility to many users.

  The avatars 174a to 174c are character images or the like that visually express the contributor of the word-of-mouth information. The avatars 174a to 174c are configured such that each poster can set appearances and decorations according to his / her preference. At this time, it is possible to identify the level of the poster from only the avatars 174a to 174c by changing the appearances and decorations that can be selected according to the level of the poster.

  Specifically, for example, the avatar 174a wears a hat with a brim, the avatar 174b wears a hat without a brim, and the avatar 174c does not wear a hat. This is because the poster represented by avatar 174a ("Mr. PQRS") has a very high level of 95 (see level icon 173a). However, since the poster (“Mr. NNNN”) represented by the avatar 174c has a level of 70 (see the level icon 173c), it can only be selected without a hat. Similarly, the poster (“Mr. MMMM”) represented by the avatar 174b has a level of 82 (see the level icon 173b), and therefore can select a favorite ornament from a brimless hat and no hat.

  In the above-described embodiment, the contributor pre-registers the area and genre that he / she is good at. However, the present invention is not limited to this, and the information management unit 53 of the information storage server 50 can post the post. Among the regions and genres corresponding to restaurants where the user has posted reviews in the past, the most frequently posted regions and genres are detected, and the detected regions and genres are set as the poster's favorite regions and genres. It is good as well.

  In addition, among the processes described in the above embodiment, all or part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed can be performed. All or a part can be automatically performed by a known method.

  In addition, the processing procedure, control procedure, specific name, and information including various data and parameters shown in the above-described document and drawings can be arbitrarily changed unless otherwise specified.

  Each component of each illustrated device is functionally conceptual and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured.

  Furthermore, all or some of the processing functions performed in each device may be realized by a CPU and a program that is analyzed and executed by the CPU, or may be realized as hardware by wired logic.

  As described above, the evaluation information management system, the evaluation information management program, and the posting information management method according to the present invention can improve the operability of the contributor without deteriorating operability even if the number of contributors increases. This is useful for an evaluation information management system in which evaluation can be easily confirmed and browsing is required to be improved.

It is a figure explaining the structure of the information provision system 20 which concerns on a present Example. It is a figure which shows an example of the top screen 100 which receives the output request of restaurant information. It is a figure which shows an example of the restaurant ranking output screen 110 according to area. It is a figure which shows an example of the word-of-mouth information output screen. 5 is a diagram illustrating an example of a posting acceptance screen 130. FIG. It is a figure which shows an example of the author review contribution log | history output screen. It is a figure which shows an example of the contributor ranking output screen. It is a figure explaining the arrow which shows the support rate change of the status icons 160a-160c. It is a figure which shows an example of the support rate log | history output screen. It is a figure explaining drag and drop operation of status icons 151a-151d. It is a figure which shows an example of the shop data 52a shown in FIG. It is a figure which shows an example of the contributor data 52b shown in FIG. It is a figure which shows an example of the posting data 52c shown in FIG. It is a figure which shows an example of the specialty area store evaluation data 52d shown in FIG. It is a figure which shows an example of the contributor evaluation data 52f shown in FIG. It is a figure which shows an example of the support rate log | history data 52g shown in FIG. It is a figure which shows an example of the contributor ranking data 52h shown in FIG. It is a figure which shows an example of the icon determination data 62a shown in FIG. It is a flowchart which shows the process sequence of the word-of-mouth information total process which concerns on a present Example. It is a figure explaining the process sequence of the shop evaluation information total process shown in FIG. It is a figure explaining the process sequence of the contributor evaluation information total process shown in FIG. It is a flowchart which shows the process sequence of the restaurant information provision process which concerns on a present Example. It is a block diagram which shows the hardware constitutions of the computer 200 which implement | achieves word-of-mouth information management processing. It is a figure which shows an example of the word-of-mouth information output screen.

Explanation of symbols

10a to 10c User terminal 20 Information providing system 30, 70 Network 40 Information providing server 41 Communication processing unit 42 Storage unit 42a Content data 42b User data 43 Information providing processing unit 44 Control unit 50 Information storage server 51 Communication processing unit 52 Storage unit 52a Store data 52b Poster data 52c Posting data 52d Specialty area store evaluation data 52e Store evaluation data 52f Contributor evaluation data 52g Support rate history data 52h Contributor ranking data 53 Information management unit 54 Control unit 60 Information totaling server 61 Communication processing unit 62 Storage unit 62a Icon determination data 63 Store evaluation information totaling unit 64 Contributor evaluation information totaling unit 65 Control unit

Claims (8)

An evaluation information management system that manages evaluation information indicating an evaluation for a poster who posts information,
Storage means for storing information posted by the poster in association with the identification information of the poster;
Support number counting means for counting the number of times that the viewer of the information posted by the poster has performed an operation to support the information as an evaluator as a support number;
An unsupported number counting means for counting the number of times that a viewer of information posted by a poster performed an operation that does not support the information as an evaluator as an unsupported number;
For each contributor, a post number counting means for counting the number of posts that is the total number of information posted by the contributor,
For each contributor, a support total counting means for totaling the total number of support for the information posted by the poster,
For each contributor, an unsupported total counting means for totaling the total number of unsupported numbers for the information posted by the poster,
For each contributor, a support rate calculating means for calculating a support rate that is a ratio occupied by the total number of the support numbers out of the total number of the total number of support and the total number of non-supports;
Icon information generating means for generating information of an icon that is a color icon corresponding to one of the size of the number of posts and the support rate and includes characters corresponding to the size of the other for each contributor,
Information output means for outputting the icon information generated by the icon information generating means together with the identification information of the poster corresponding to the icon;
An evaluation information management system characterized by comprising: A support rate history storage unit that stores a history of the support rate calculated by the support rate calculating unit;
A support rate fluctuation specifying unit for specifying a change in the support rate based on the past support rate stored in the support rate history storage unit and the new support rate calculated by the support rate calculating unit,
The icon generated by the icon information generating means is
The evaluation information management system according to claim 1, further comprising: a symbol representing a change in the support rate specified by the support rate change specifying unit. Comprising a poster ranking creating means for creating a poster ranking in which the corresponding icons and the identification information are arranged in order from a poster having a large product of the number of posts and the support rate,
The evaluation information management system according to claim 1, wherein the information output unit outputs the poster ranking created by the poster ranking creation unit. The information posted by the contributor is word-of-mouth information for the store,
Search means for searching for word-of-mouth information for a common store among word-of-mouth information of each contributor corresponding to each designated icon when a plurality of icons are designated among the icons output by the information output means. Prepared,
The evaluation information management system according to any one of claims 1 to 3, wherein the information output means outputs the word-of-mouth information searched by the search means . Level determining means for determining the level of the poster based on the support and non-support operations by the evaluator performed on the information posted by the poster,
Generating means for generating information for displaying the information posted by the contributor in a display form corresponding to the level determined by the level determining means for the contributor,
The evaluation information management system according to claim 1 , wherein the information output unit outputs information generated by the generation unit . The level of the contributor is
6. The evaluation information management system according to claim 5 , wherein the evaluation information management system is determined based on a level of the evaluator who performs the support or non-support operation . An evaluation information management program for causing a computer to manage evaluation information indicating an evaluation for a contributor who posts information,
The computer,
Storage processing means for storing information posted by a poster in association with identification information of the poster and storing the information in a storage device;
Number of support counting means for counting the number of times that the viewer of the information posted by the poster has performed an operation to support the information as an evaluator as the number of support,
Unsupported number counting means for counting the number of times the viewer of the information posted by the user performed an operation that does not support the information as an evaluator as the number of unsupported,
For each contributor, a post number counting means for totaling the number of posts that is the total number of information posted by the contributor,
For each contributor, a support total counting means for totaling the total number of support for the information posted by the poster,
For each contributor, an unsupported total counting means for summing up the total number of unsupported for the information posted by the poster,
A support rate calculating means for calculating a support rate, which is a ratio of the total number of the supported numbers out of the total number of the total number of the supported numbers and the total number of the unsupported numbers for each contributor,
Icon information generating means for generating, for each contributor, information of an icon that is a color icon according to the size of either one of the number of posts and the support rate and that includes characters according to the size of the other,
Information output means for outputting the icon information generated by the icon information generating means together with the identification information of the poster corresponding to the icon;
An evaluation information management program characterized by functioning as An evaluation information management method in which a computer system manages evaluation information indicating an evaluation for a contributor who posts information,
A storage processing step for storing information posted by the poster in the storage device in association with the identification information of the poster;
The support number counting step of counting the number of times that the viewer of the information posted by the poster performed an operation to support the information as an evaluator as the support number,
An unsupported number counting step of counting the number of times the viewer of the information posted by the poster performed an operation that does not support the information as an evaluator as an unsupported number;
For each contributor, a post number counting step of counting the number of posts that is the total number of information posted by the contributor,
For each contributor, a total support number counting step of totaling the total number of support for the information posted by the contributor,
For each contributor, an unsupported total number counting step of counting the total number of unsupported numbers for the information posted by the poster,
For each contributor, a support rate calculation step of calculating a support rate that is a ratio occupied by the total number of the support number out of the total number of the total number of support and the total number of non-support.
An icon information generating step for generating information of an icon that is a color icon according to the size of either one of the number of posts and the support rate and includes characters according to the size of the other for each contributor,
An evaluation information management method , wherein the computer system executes each step of an information output step of outputting information on the icon generated by the icon information generation step together with identification information of a poster corresponding to the icon .

Images