Information processing device, social VR system, information processing method, and information processing program

Abstract

Provided is an information processing device, etc., with which it is possible to provide a virtual space in which a user can easily find an unknown user who has the same interests or concerns as the user. This information processing device includes: a section information acquisition means for acquiring section information relating to a section in a virtual space; a group detection means for detecting a group formed by a plurality of users for each section; a group feature quantity extraction means for extracting a group feature quantity, which is a feature quantity of the group; and a tag display means for displaying, for each section, a tag that displays the group feature quantity.

Description

Information processing device, social VR system, information processing method, and recording medium

[0001] The present disclosure relates to an information processing device, a social VR system, an information processing method, and an information processing program.

[0002] In recent years, communication using virtual spaces on the Internet has become popular. When using a virtual space, for example, an avatar representing a user is generated in the virtual space. Then, this avatar communicates with avatars of other users within the virtual space. This enables communication between multiple users via the virtual space. Methods for supporting such communication have been studied. For example, Patent Literature 1 discloses a technology for controlling communication between avatars based on the distance within the virtual space. In this technology, a unique area is first set around each avatar. Then, when the unique area of ​​one user's avatar overlaps with the unique area of ​​another user's avatar, a message exchange session is established. This technology enables communication between users whose avatars are nearby in the virtual space.

[0003] Furthermore, Patent Document 2 discloses a technology for supporting communication between multiple avatars gathered for a specific purpose. In this technology, character information of characters (avatars) gathered in a party in a virtual space is first displayed in a predetermined position on a display screen. In addition, text information entered for each character is displayed in an area adjacent to the character information. This allows the information required by the player (user) to be displayed accurately and realistically. It also discloses that this does not impair the operability of the game.

[0004] JP 2003-067317 A JP 2014-023940 A

[0005] In the technology of Patent Document 1, the avatars that a user can meet are limited to those that are nearby in the virtual space. Therefore, the user of the other avatar may not necessarily have the same interests or concerns as the user. In other words, there is a problem in that the probability of meeting a user who has the same interests or concerns as the user is dependent on chance.

[0006] Furthermore, in the technology of Patent Document 2, users who can be met are limited to users who agree with a predetermined purpose, which poses a problem of fewer opportunities to meet unknown users who share the same interests and concerns as the user.

[0007] The present invention has been made in consideration of the above-mentioned problems, and aims to provide an information processing device, etc. that can provide a virtual space in which users can easily discover unknown users who have the same interests and concerns as them.

[0008] In order to solve the above problems, the information processing device of the present disclosure includes a partition information acquisition means for acquiring partition information regarding partitions in a virtual space, a group detection means for detecting groups formed by multiple users for each partition, a group feature extraction means for extracting group features that are features of the groups, and a tag display means for displaying tags that indicate the group features for each partition.

[0009] A social VR (Virtual Reality) system according to the present disclosure includes the information processing device described above and a virtual space generation server that generates the virtual space.

[0010] In addition, the information processing method disclosed herein includes an information processing device that acquires partition information regarding partitions in a virtual space, detects groups formed by multiple members for each partition, extracts group features that are characteristics of the groups, and displays tags that display the group features for each partition.

[0011] In addition, the information processing program disclosed herein causes a computer to execute the following processes: acquiring partition information regarding partitions in a virtual space; detecting groups formed by multiple members for each partition; extracting group features that are characteristics of the groups; and displaying tags that display the group features for each partition.

[0012] The effect of the present invention is to provide an information processing device or the like that can provide a virtual space in which a user can easily find unknown users who have the same interests and concerns as the user.

[0013] 1 is a block diagram showing an example of an information processing device. FIG. 2 is a block diagram showing an example of a social VR system. FIG. 3 is a flowchart showing an example of the operation of the information processing device. FIG. 4 is a block diagram showing an example of a group feature extraction means. FIG. 5 is a schematic diagram showing an example of a display of a virtual space. FIG. 6 is a block diagram showing an example of a participating user feature extraction means. FIG. 7 is a block diagram showing an example of a behavior history feature extraction means. FIG. 8 is a block diagram showing an example of the hardware configuration of an information processing device. FIG. 9 is a block diagram showing an example of an information processing device of a modified example. FIG. 10 is a block diagram showing an example of a player feature extraction means. FIG. 11 is a flowchart showing an example of the operation of the information processing device of a modified example.

[0014] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. However, the embodiments described below are limited to technically preferable aspects for implementing the present disclosure, but are not intended to limit the scope of the disclosure to the following. Note that similar components in each drawing are given the same numbers, and descriptions thereof may be omitted.

[0015] 1 is a block diagram showing an example of an information processing device 100. The information processing device 100 includes a block information acquisition unit 10, a group detection unit 20, a group feature extraction unit 30, and a tag display unit 40.

[0016] The partition information acquisition means 10 acquires partition information relating to partitions in the virtual space. The partitions are set to identify locations in the virtual space. By acquiring the partition information, the partition information acquisition means 10 can link other information to locations in the virtual space. For example, partitions are formed by dividing the virtual space into a grid.

[0017] For each section, the group detection means 20 detects groups formed by multiple users. In this embodiment, it is assumed that users can communicate with each other using, for example, the following mechanism: Each user uses an avatar that can move within the virtual space. When one avatar approaches another, the avatars (users) can communicate with each other. Methods of communication include, for example, voice conversation, exchanging text messages, and sharing files.

[0018] The group detection means 20 detects that the above-described communication-related data has been generated. This detection then detects the formation of a group. As described above, in the virtual space of this embodiment, avatars can communicate with each other when they come close to each other. Therefore, each group is linked to a section within the virtual space. In other words, various groups can be formed for each section.

[0019] When a group is detected, the group feature extraction means 30 extracts a group feature for each group. Specific group features will be described later, but examples of group features include topics discussed in the group and attributes common to the users who form the group.

[0020] Then, the tag display means 40 displays a tag indicating the extracted group feature in the corresponding section.

[0021] The above configuration makes it easy for users to find groups that match their interests. The reasons for this are as follows: When the virtual space is large and the number of participants is large, it becomes difficult to find an area with a group that matches their interests. Also, when contacting nearby groups randomly, users have to spend time checking whether the group's topics match their interests. Furthermore, there is a risk that users will end up participating in conversations they do not want to be involved in.

[0022] On the other hand, in the configuration of this embodiment, the user can easily understand the characteristics of the groups formed in each section by looking at the tags, and as a result, the user can easily find groups that interest or concern them.

[0023] 2 is a block diagram showing an example of a social VR system 1000. The social VR system 1000 includes an information processing device 100 and a virtual space generation server 200 according to this embodiment.

[0024] The virtual space generation server 200 generates a virtual space. The virtual space is divided into sections corresponding to addresses in the real world. Furthermore, the virtual space generation server 200 generates and controls avatars in response to user requests. The virtual space also provides an environment that allows avatars (users) to communicate with each other. For example, communication is possible when one avatar approaches another avatar within a predetermined contact distance. Communication methods include, for example, exchanging text messages, voice conversations, and displaying files. The information processing device 100 then displays tags representing group features in each section. Natural landforms such as mountains and oceans, buildings, stores, stations, and objects may also be generated in the virtual space.

[0025] A user accesses the social VR system 1000 using a user terminal 2000. The user then logs in to the virtual space using an avatar. The user terminal 2000 has the calculation function, storage function, and communication function of a general computer. The user terminal 2000 also has a display device 2100 and an input / output device 2200. The display device 2100 and the input / output device 2200 may be separate devices. The display device 2100 and the input / output device 2200 may also be integrated. The display device 2100 is, for example, a head-mounted display (HMD) or a flat panel display. Using an HMD enhances the user's sense of immersion and realism.

[0026] Furthermore, an avatar in a virtual space is controlled by a user operating the input / output device 2200. For example, the movement of an avatar in a virtual space is executed by a user operating the input / output device 2200. Furthermore, for example, the input / output device 2200 may include an audio input unit and a speaker, thereby enabling audio input and output. This allows, for example, audio conversations to be held in the virtual space.

[0027] Next, the operation of the information processing device 100 will be described. FIG. 3 is a flowchart showing an example of the operation of the information processing device 100. First, the information processing device 100 acquires partition information from the virtual space generation server 200 (S101). Next, the group detection means 20 detects groups formed in each partition (S102). At this time, the users participating in each group are also identified. User information is stored, for example, in the virtual space generation server 200. In this way, the formed groups are identified by linking them to the partitions in the information processing device 100. Then, the group feature extraction means 30 acquires user information of the users participating in each group. Next, the group feature extraction means 30 extracts features of each group. The group features are extracted as group features (S103). Details of the group features will be described later. Next, the extracted group features are displayed as tags in the virtual space (S104). Note that, for example, the extraction of group features is repeated at a predetermined extraction cycle. Furthermore, the tag display is updated, for example, at a predetermined update cycle.

[0028] As described above, according to the configuration of this embodiment, the characteristics of the groups formed in each section are displayed in tags. By referring to these tags, users can easily find groups that interest them.

[0029] (Specific Example 1) Next, a specific example of group features and the group feature extraction means 30 will be described. Fig. 4 is a block diagram showing an example of the group feature extraction means. The group feature extraction means 30 in this example includes a frequently occurring word extraction means 31 and a participating user feature extraction means 32.

[0030] The frequent word extraction means 31 extracts words that frequently appear in communication between groups formed in a certain section. First, the frequent word extraction means 31 records words that appear in messages and conversations during a predetermined frequent word extraction period. When a conversation is conducted by voice, the frequent word extraction means 31 records characters converted from the spoken words. Next, the recorded words are ranked according to their frequency of appearance. Then, a predetermined number of words are selected in descending order of rank as frequently appearing words to be displayed in tags.

[0031] FIG. 5 is a schematic diagram showing an example of a virtual space display. The virtual space is divided into grid-like sections. Group a is formed in section a (x1, y1). Group b is formed in section b (x2, y2). Here, the user's (own) avatar is located in section c (x3, y3), which is separate from sections a and b. In section a, frequently used words "war," "Takeda Shingen," and "Kawanakajima" are displayed in tag a. In section b, "baseball," "Ohtani," and "tickets" are displayed in tag b. By referring to these tags, the user can easily find groups that interest them. Then, by moving to a section of interest, the user can communicate with the group formed there.

[0032] (Specific Example 2) Group features may include features common to users participating in each group. The participating user feature extraction means 32 then extracts these features as participating user features. The user features include features of the user's profile and features of the user's behavior. Therefore, the participating user feature extraction means 32 extracts profile features and behavior features. To this end, the participating user feature extraction means 32 includes user information acquisition means 321. The participating user feature extraction means 32 also includes profile feature extraction means 322. The participating user feature extraction means 32 also includes behavior history feature extraction means 323. Figure 6 is a block diagram showing an example of the participating user feature extraction means 32.

[0033] The user information acquisition means 321 acquires user information of users participating in a group. For example, the user information is acquired from the virtual space generation server 200. Here, for example, the user information is stored in the social VR system 1000. For example, when using the social VR system 1000, each user registers their own profile information in the system. The profile information includes, for example, hobbies, interests, and concerns.

[0034] The profile feature extraction means 322 extracts profiles common to the users participating in this group. For example, if many users in a certain group have "watching baseball" registered as a hobby in their profile information, then "watching baseball" is extracted as the profile information for this group. Also, if many users have "mountain climbing" registered as an interest, then "mountain climbing" is extracted as the profile information for this group. The profile information is then ranked in descending order of the number of common users. Next, a predetermined number of profile information is extracted in descending order of rank as profile features to be displayed in tags.

[0035] Furthermore, if each user information contains a user's behavior history, a behavior history feature is extracted. The behavior history feature is a feature of the behavior history common to the users participating in the group. The behavior history feature extraction means 323 extracts the behavior history feature. Note that this behavior history is a behavior history in the virtual space.

[0036] 7 is a block diagram showing an example of the behavior history feature extraction means 323. The behavior history feature extraction means 323 includes a participation group feature extraction means 3231, an uttered word feature extraction means 3232, and an object involvement feature extraction means 3233.

[0037] The participating group feature extraction means 3231 extracts participating group features related to groups that each user has participated in in the past. For example, the behavior feature includes the group that the user stayed in in the past, the group feature of that group, and the user's stay time in that group. Then, for example, the groups are ranked according to the stay time, and the feature of the top group is extracted as the participating group feature.

[0038] The uttered word feature extraction means 3232 extracts the feature of words uttered by each user. For example, here, the uttered word feature includes words that frequently appear in messages uttered by each user in text or voice. In other words, words uttered in message exchanges carried out within a group are ranked according to the number of times they appear. Then, the words with the highest rankings are extracted as the uttered word feature.

[0039] The behavior history may also include each user's involvement with objects in the virtual space. The object involvement feature extraction means 3233 extracts features of this involvement with the object. The features of the involvement with the object are extracted as object involvement features. Objects include, for example, natural landforms such as mountains and the sea, buildings, stores, stations, and objects. The user's involvement with the object includes, for example, touching the object, gazing at the object, and the like. The involvement with the object is then ranked according to, for example, the number of involvements, the duration of the involvement, and the like. In one example, the features are ranked according to the cumulative involvement time, which is the cumulative involvement time, and the features with the highest rankings are extracted as object involvement features.

[0040] The above-mentioned participating group feature, uttered word feature, and object involvement feature are assigned to the tag, and the tag is then displayed in the corresponding section.

[0041] As described above, according to the configuration of Example 2, the profile and behavioral history of each user constituting a group are reflected in the group feature. The group feature is then displayed as a tag. This allows a user who has just logged in to the virtual space to easily find a group that matches their interests.

[0042] Next, a description will be given of the hardware configuration of the information processing device 100. FIG. 8 is a block diagram showing an example of the hardware configuration of the information processing device 100.

[0043] The information processing device 100 is implemented in, for example, a general-purpose computer. This computer includes, for example, a processor 110, a memory 120, a display unit 130, an input / output unit 140, a storage unit 150, and a communication interface 160. The processor 110 performs calculations necessary for information processing such as tag display. The memory 120 stores data used in the calculations. The display unit 130 displays data and images. The input / output unit 140 is a device that inputs and outputs data. The input / output unit 140 includes, for example, a keyboard, a mouse, an audio signal output unit, and a print signal output unit. The storage unit 150 stores data. The communication interface 160 performs interface processing for communication. The above hardware configuration enables the control necessary for information processing.

[0044] (Modification) In Specific Example 1 and Specific Example 2, a method for displaying group feature amounts as tags in each section was described. If group feature amounts for all groups are displayed as tags using this method, the number of tags will increase as the number of groups formed increases. When the number of tags becomes enormous, it becomes difficult for users searching for groups to join to find groups that match their interests. Therefore, in a modification, a configuration for narrowing down the tags to be displayed will be described. In the following description, users who are considering joining will be referred to as players in order to distinguish between users who are already participating in groups and users who are searching for groups to join.

[0045] 9 is a block diagram showing an example of an information processing device 101 according to a modified example. Like the information processing device 100, the information processing device 101 has a section information acquisition means 10, a group detection means 20, and a group feature extraction means 30. In addition, it has a player feature acquisition means 33. Furthermore, tag display means 40a has a feature comparison means 41. Note that a description of the same components as those of the information processing device 100 will be omitted.

[0046] The player characteristic quantity acquisition means 33 acquires player characteristic quantities. Fig. 10 is a block diagram showing an example of the player characteristic quantity acquisition means 33. The player characteristic quantity acquisition means 33 includes a player information acquisition means 331, a player profile characteristic quantity extraction means 332, and a player action history characteristic quantity extraction means 333.

[0047] The player information acquisition means 331 acquires player information. The player information is similar to the user information in the information processing device 100. In other words, the player information includes the player's profile information and the player's behavior history in the virtual space. The player information is stored, for example, in the virtual space generation server 200. Alternatively, the player information may be stored in the user terminal 2000. Then, the player information acquisition means 331 acquires this player information.

[0048] From the acquired player information, the player profile feature extraction means 332 extracts player profile features. The player profile features include, for example, the hobbies and interests registered by the player.

[0049] Furthermore, the player behavior history feature extraction means 333 extracts behavior history features from the acquired player information. This behavior history is the player's behavior history in the virtual space. The player behavior history features are the same as the user behavior history features in the information processing device 100. In other words, the behavior history features include, for example, the player's participation group features, the player's uttered word features, and the object involvement features.

[0050] The participating group feature is a feature of a group that the player has stayed in in the past. For example, the groups are ranked according to the player's stay time, and the feature of the top group is extracted as the participating group feature.

[0051] Furthermore, the player action history feature extraction means 333 extracts the feature quantities of words uttered by the player. In the virtual space, the player utters messages in text or voice. For example, the player action history feature extraction means 333 extracts words that have appeared frequently in messages uttered by the player in the past. In other words, words are ranked according to the number of times they have appeared in messages uttered by the player. Then, the words with the highest rankings are extracted as uttered word feature quantities.

[0052] The behavior history may also include the player's involvement with objects in the virtual space. The feature of this involvement with the object is extracted by the player behavior history feature extracting means 333. For example, an object with a long cumulative involvement time by the player is extracted as the object involvement feature.

[0053] The player action history feature extracting means 333 extracts player action history feature amounts including the above-mentioned participating group feature amount, uttered word feature amount, and object involvement feature amount.

[0054] With the above configuration, the player characteristic amount acquisition means 33 acquires player characteristic amounts. Next, the characteristic amount comparison means 41 compares the group characteristic amounts with the player characteristic amounts. Next, the characteristic amount comparison means 41 sets a group having a group characteristic amount that matches the player characteristic amount as a tag display candidate. Then, the tag display means 40a displays the characteristic amounts of the group set as the tag display candidate in a tag.

[0055] FIG. 11 is a flowchart showing an example of the operation of the information processing device 101 of the modified example. First, the information processing device 101 acquires partition information of the virtual space (S201). Next, the group detection means 20 detects groups formed in each partition (S202). Next, the group characteristic extraction means 30 extracts characteristics of each group. These characteristics are extracted as group characteristics (S203). Next, the player characteristic acquisition means 33 acquires player characteristics (S204). Next, the characteristic comparison means 41 compares the player characteristics with the group characteristics. Then, the characteristic comparison means 41 sets groups whose group characteristics match the player characteristics as tag display candidates (S205). Next, the tag display means 40a displays the group characteristics of the tag display candidate groups in tags in the virtual space (S206). Through the above operations, only tags of groups whose group characteristics match the player characteristics are displayed in the virtual space. As a result, the groups for which tags are displayed are narrowed down to groups that the player is interested in.

[0056] As described above, according to the information processing device 101 of the modified example, groups for which tags are displayed in the virtual space are narrowed down to groups that the player is interested in. This makes it easier for the player to search for groups that interest them.

[0057] The information processing device and the like according to this embodiment have been described above.

[0058] The information processing device 100 of this embodiment includes a partition information acquisition means 10, a group detection means 20, a group feature extraction means 30, and a tag display means 40. The partition information acquisition means 10 acquires partition information relating to partitions in a virtual space. The group detection means 20 detects groups formed by multiple users for each partition. The group feature extraction means 30 extracts group features, which are features of the groups. The tag display means 40 displays tags indicating the group features for each partition.

[0059] With the above configuration, the characteristics of groups formed in the virtual space are displayed in tags for each section. By referring to these tags, users searching for groups can easily find the group they are looking for.

[0060] According to one aspect, in the information processing device 100, the group features include words that frequently appear in message exchanges in each of the groups.

[0061] With the above configuration, words that are trending in each group are displayed in the tags, making it easier to find groups that are discussing topics that interest you.

[0062] According to one aspect, the group feature amount includes a participating user feature amount in the information processing device 100. The participating user feature amount is extracted from user information of each user participating in the group.

[0063] According to the above configuration, the characteristics of the users participating in each group are displayed in the tags, making it easy to find groups of users who share the same interests as you.

[0064] According to one aspect, in the information processing device 100, the user information includes profile information preset by the user.

[0065] According to the above configuration, the profile characteristics of the users participating in each group are displayed in the tag, making it easy to find a group that brings together users who match your preferences.

[0066] According to one aspect, in the information processing device 100, the user information includes behavior history information regarding the behavior history of the user in the virtual space.

[0067] According to the above configuration, the characteristics of the behavioral history of users participating in each group are displayed in the tag, making it easy to find a group of users who engage in behavior that matches your preferences.

[0068] According to one aspect, in the information processing device, the behavior history includes past utterances of the user.

[0069] According to the above configuration, the characteristics of past utterances of users participating in each group are displayed in tags, making it easy to find groups that contain users who make utterances that match your preferences.

[0070] According to one aspect, the information processing device 101 includes a player characteristic amount acquisition means 33 and a characteristic amount comparison means 41. A player is a user searching for a group that matches a purpose. The player characteristic amount acquisition means 33 acquires a player characteristic amount related to this player. The characteristic amount comparison means 41 compares the player characteristic amount with the group characteristic amount. Then, the tag display means 40a displays the tag of the group having the group characteristic amount that matches the player characteristic amount.

[0071] With the above configuration, only the tags of groups with group characteristics that match the characteristics of the player are displayed in the virtual space. This narrows down the groups that display tags to those that interest the player, making it easier for the player to find groups they want to join.

[0072] The social VR system 1000 of this embodiment includes the information processing device 100 and a virtual space generation server 200. The virtual space generation server 200 generates a virtual space. Here, VR is an abbreviation for Virtual Reality.

[0073] The above configuration makes it easier for a user (player) searching for a group to contact in the virtual space to search for a group that meets their desires.

[0074] In the information processing method of this embodiment, the information processing device 100 acquires partition information relating to partitions in a virtual space. The information processing device 100 also detects groups formed by multiple users for each partition. The information processing device 100 also extracts features of the groups. The information processing device 100 also displays tags indicating the features of the groups for each partition.

[0075] With the above configuration, the characteristics of groups formed in the virtual space are displayed in tags for each section. By referring to these tags, users searching for a group they would like to join can easily find the group they are looking for.

[0076] The information processing program of this embodiment causes a computer to execute a process of acquiring partition information about partitions in a virtual space and a process of detecting groups formed by multiple users for each partition. The information processing program also causes the computer to execute a process of extracting features of the groups. The information processing program also causes the computer to execute a process of displaying tags for each partition. At this time, the tags display the features of the groups.

[0077] With the above configuration, the characteristics of groups formed in the virtual space are displayed in tags for each section. By referring to these tags, users searching for groups can easily find the group they are looking for.

[0078] The scope of the present invention also includes a program that causes a computer to execute any of the processes disclosed above, and a recording medium storing the program. Examples of recording media that can be used include a magnetic disk, a magnetic tape, an optical disk, a magneto-optical disk, and a semiconductor memory.

[0079] The present disclosure has been described above using the first embodiment as an exemplary example. However, the present disclosure is not limited to the above embodiment. That is, the present disclosure can be applied in various aspects that can be understood by a person skilled in the art within the scope of the present disclosure.

[0080] Some or all of the above embodiments can be described as follows: However, the scope of the present disclosure is not limited to the following.

[0081] (Supplementary Note 1) An information processing device comprising: a partition information acquisition means for acquiring partition information relating to partitions in a virtual space; a group detection means for detecting groups formed by multiple users for each of the partitions; a group feature extraction means for extracting group features that are features of the groups; and a tag display means for displaying tags that indicate the group features for each of the partitions.

[0082] (Supplementary Note 2) The information processing device according to Supplementary Note 1, wherein the group feature includes a word that frequently appears in message exchanges in each of the groups.

[0083] (Supplementary Note 3) The information processing device according to Supplementary Note 1 or 2, wherein the group feature includes a participating user feature extracted from user information related to each of the users participating in the group.

[0084] (Supplementary Note 4) The information processing device according to Supplementary Note 3, wherein the user information includes profile information preset by the user.

[0085] (Supplementary Note 5) The information processing device according to Supplementary Note 3 or 4, wherein the user information includes behavior history information regarding a behavior history of the user in the virtual space.

[0086] (Supplementary Note 6) The information processing device according to Supplementary Note 5, wherein the behavior history includes content of past utterances of the user.

[0087] (Supplementary Note 7) The information processing device according to Supplementary Note 5 or 6, wherein the behavior history includes a history of the user's involvement with an object provided in the virtual space.

[0088] (Supplementary Note 8) An information processing device as described in any one of Supplementary Notes 1 to 7, comprising: a player characteristic acquisition means for acquiring player characteristics related to a player who is a user searching for a group to join; and a characteristic comparison means for comparing the player characteristic with the group characteristic, wherein the tag display means displays the tag of the group having the group characteristic that matches the player characteristic.

[0089] (Supplementary Note 9) A social VR (Virtual Reality) system comprising: an information processing device according to any one of Supplements 1 to 8; and a virtual space generation server that generates the virtual space.

[0090] (Supplementary Note 10) An information processing method, characterized in that an information processing device acquires partition information regarding partitions in a virtual space, detects groups formed by multiple users for each partition, extracts features of the groups, and displays tags indicating the features of the groups for each partition.

[0091] (Supplementary Note 11) An information processing program causing a computer to execute the following processes: acquiring partition information about partitions in a virtual space; detecting groups formed by multiple users for each partition; extracting features of the group; and displaying tags indicating the features of the group for each partition. The present invention has been described above using the above-mentioned embodiment as an exemplary example. However, the present invention is not limited to the above-mentioned embodiment. In other words, the present invention can be applied in various aspects that are understandable to those skilled in the art within the scope of the present invention. This application claims priority based on Japanese Patent Application No. 2023-096810, filed on June 13, 2023, the entire disclosure of which is incorporated herein by reference.

[0092] REFERENCE SIGNS LIST 10: Boundary information acquisition means 20: Group detection means 30: Group feature extraction means 31: Frequently used word extraction means 32: Participating user feature extraction means 33: Player feature acquisition means 40, 40a: Tag display means 41: Feature comparison means 100, 101: Information processing device 200: Virtual space generation server 1000: Social VR system 2000: User terminal 2100: Display device 2200: Input / output device

Claims

1. a section information acquisition means for acquiring section information relating to a section in the virtual space; a group detection means for detecting a group formed by a plurality of users for each of the sections; a group feature extraction means for extracting a group feature that is a feature of the group; a tag display means for displaying a tag indicating the group feature for each of the sections; An information processing device comprising:

2. The group feature is containing words that frequently appear in message exchanges in each of the groups, 2. The information processing apparatus according to claim 1, wherein:

3. The feature amount of the group is including participating user features extracted from user information regarding each of the users participating in the group; 3. The information processing apparatus according to claim 1, wherein the information processing apparatus is a computer.

4. The user information is including profile information preset by the user; 4. The information processing apparatus according to claim 3,

5. The user information is including behavior history information regarding the user's behavior history in the virtual space; 4. The information processing apparatus according to claim 3,

6. The behavioral history is Including the user's past utterances, 6. The information processing apparatus according to claim 5,

7. The behavioral history is a history of the user's involvement with an object provided in the virtual space; 6. The information processing apparatus according to claim 5,

8. a player characteristic amount acquisition means for acquiring a player characteristic amount relating to a player who is the user searching for the group in which the user wishes to join; a feature comparison means for comparing the player feature with the group feature, The tag display means displaying the tag of the group having the group feature that matches the player feature; 2. The information processing apparatus according to claim 1, wherein:

9. The information processing device according to claim 1 or 2; a virtual space generation server that generates the virtual space; A social VR (Virtual Reality) system comprising:

10. The information processing device obtaining parcel information about a parcel in the virtual space; detecting a group formed by a plurality of users for each of the sections; extracting a group feature that is a feature of the group; displaying a tag indicating the group feature for each of the sections; An information processing method comprising:

11. The group feature is containing words that frequently appear in message exchanges in each of the groups, 11. The information processing method according to claim 10.

12. The feature amount of the group is including participating user features extracted from user information regarding each of the users participating in the group; 11. The information processing method according to claim 10.

13. The user information is including profile information preset by the user; 13. The information processing method according to claim 12.

14. The user information is including behavior history information regarding the user's behavior history in the virtual space; 13. The information processing method according to claim 12.

15. The behavioral history is Including the user's past utterances, 15. The information processing method according to claim 14.

16. The behavioral history is a history of the user's involvement with an object provided in the virtual space; 15. The information processing method according to claim 14.

17. The information processing device acquire player features related to the player who is the user searching for the group in which he or she wishes to join; comparing the player characteristics with the group characteristics; displaying the tag of the group having the group feature that matches the player feature; 17. The information processing method according to claim 10,

18. obtaining parcel information relating to a parcel in the virtual space; A process of detecting a group formed by a plurality of users for each of the sections; A process of extracting group features that are features of the group; a process of displaying a tag indicating the group feature for each of the sections; An information processing program characterized by causing a computer to execute the above.

19. The group feature is containing words that frequently appear in message exchanges in each of the groups, 19. The information processing program according to claim 18.

20. The feature amount of the group is including participating user features extracted from user information regarding each of the users participating in the group; 19. The information processing program according to claim 18.

21. The user information is including profile information preset by the user; 21. The information processing program according to claim 20.

22. The user information is including behavior history information regarding the user's behavior history in the virtual space; 21. The information processing program according to claim 20.

23. The behavioral history is Including the user's past utterances, 23. The information processing program according to claim 22.

24. The behavioral history is a history of the user's involvement with an object provided in the virtual space; 23. The information processing program according to claim 22.

25. Acquiring player characteristics related to a player who is the user searching for the group in which he or she wishes to join; comparing the player characteristics with the group characteristics; displaying the tag of the group having the group feature that matches the player feature; 25. The information processing program according to claim 18, wherein the program causes a computer to execute the steps of: