Information processing apparatus, method, program, and system

Abstract

To realize diagnosis of organizational characteristics with low costs and with less time lag.SOLUTION: A program according to an embodiment of the present invention causes a computer to function as: means for acquiring use state data of organization members in a chat tool; means for, based on the use state data, analyzing a communication state in a unit period as an analysis unit at least partially different in human arrangement from the organization in view of relationship between organization members included in the analysis unit and other persons included in the analysis unit; means for diagnosing characteristics of the organization based on the analysis result of the communication state; and means for outputting a diagnosis result of the organization characteristics.SELECTED DRAWING: Figure 4

Description

Technical Field

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

Background Art

[0002] Organizational diagnosis based on questionnaire responses from organizational members can obtain appropriate results by appropriately designing the questionnaire. However, such organizational diagnosis is costly and prone to low implementation frequency, so it is impossible to grasp changes in organizational characteristics in real time, and for example, it is difficult to verify the effects of measures for organizational improvement.

[0003] Patent Document 1 discloses a technical idea intended to analyze organizational communication and determine organizational rigidity.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] The technical idea described in Patent Document 1 may be useful for diagnosing organizational characteristics (personality) from the perspective of organizational rigidity, but it cannot be directly applied to diagnosing organizational characteristics from other perspectives.

[0006] An object of the present disclosure is to realize diagnosis of organizational characteristics from a perspective different from the above background art at low cost and with reduced time lag.

Means for Solving the Problems

[0007] A program according to an aspect of the present disclosure causes a computer to function as means for acquiring usage data of a chat tool by members of an organization, means for analyzing a communication state in a unit period of an analysis unit whose human composition is at least partially different from that of the organization from the perspective of the relationship between the members of the organization included in the analysis unit and other persons included in the analysis unit based on the usage data, means for diagnosing characteristics of the organization based on the analysis result of the communication state, and means for outputting a diagnosis result of the characteristics of the organization.

Brief Description of Drawings

[0008]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Embodiments for Carrying Out the Invention

[0009] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. In the drawings for explaining the embodiments, the same components are generally denoted by the same reference numerals, and repeated explanations thereof are omitted.

[0010] (1) Configuration of the information processing system The configuration of the information processing system will be described. FIG. 1 is a block diagram showing the configuration of the information processing system according to the present embodiment.

[0011] As shown in FIG. 1, the information processing system 1 includes a client device 10 and a server 30. The client device 10 and the server 30 are connected via a network (for example, the Internet or an intranet) NW. Also, the client device 10 and the chat server 50 are connected via the network NW. The server 30 and the chat server 50 are connected via the network NW.

[0012] The client device 10 is an example of an information processing device. The client device 10 is, for example, a smartphone, a tablet terminal, or a personal computer. In the example of FIG. 1, the number of client devices 10 is one, but the number of client devices 10 may be two or more.

[0013] The user of the client device 10 is, for example, a member of the organization to be diagnosed. The user posts or views messages on the chat tool using the client device 10. Also, at least a part of the users (for example, users with access rights such as employees in the personnel department and management) can access the diagnosis results presented from the server 30 using the client device 10.

[0014] The server 30 is an example of an information processing device. The server 30 is, for example, a server computer.

[0015] The chat server 50 is an example of an information processing device. The chat server 50 is, for example, a server computer. The chat server 50 provides a chat tool service to the users of the client device 10.

[0016] (1-1) Configuration of the client device The configuration of the client device will be described. FIG. 2 is a block diagram showing the configuration of the client device of the present embodiment.

[0017] As shown in FIG. 2, the client device 10 includes a storage device 11, a processor 12, an input / output interface 13, and a communication interface 14. The client device 10 is connected to a display 21.

[0018] The storage device 11 is configured to store programs and data. The storage device 11 is, for example, a combination of a ROM (Read Only Memory), a RAM (Random Access Memory), and a storage (e.g., flash memory or hard disk).

[0019] The program includes, for example, the following programs. · Program of the OS (Operating System) · Program of an application that executes information processing (e.g., a web browser)

[0020] The data includes, for example, the following data. · Database referred to in information processing · Data obtained by executing information processing (i.e., the execution result of information processing)

[0021] The processor 12 is a computer that realizes the functions of the client device 10 by starting the programs stored in the storage device 11. The processor 12 is, for example, at least one of the following. · CPU (Central Processing Unit) · GPU (Graphic Processing Unit) · ASIC (Application Specific Integrated Circuit) · FPGA (Field Programmable Gate Array)

[0022] The input / output interface 13 is configured to acquire information (e.g., user instructions) from an input device connected to the client device 10 and output information (e.g., images) to an output device connected to the client device 10.

[0023] The input device is, for example, a keyboard, a pointing device, a touch panel, or a combination thereof. The output device is, for example, a display 21, a speaker, or a combination thereof.

[0024] The communication interface 14 is configured to control communication between the client device 10 and an external device (e.g., the server 30 or the chat server 50).

[0025] The display 21 is configured to display images (still images or moving images). The display 21 is, for example, a liquid crystal display or an organic EL display.

[0026] (1-2) Configuration of the server The configuration of the server will be described. FIG. 3 is a block diagram showing the configuration of the server of the present embodiment.

[0027] As shown in FIG. 3, the server 30 includes a storage device 31, a processor 32, an input / output interface 33, and a communication interface 34.

[0028] The storage device 31 is configured to store programs and data. The storage device 31 is, for example, a combination of a ROM, a RAM, and a storage (e.g., a flash memory or a hard disk).

[0029] The program includes, for example, the following programs. · An OS program · A program of an application that executes information processing

[0030] The data includes, for example, the following data. · Database referenced in information processing · Execution result of information processing

[0031] The processor 32 is a computer that realizes the functions of the server 30 by starting the program stored in the storage device 31. The processor 32 is, for example, at least one of the following. · CPU · GPU · ASIC · FPGA

[0032] The input / output interface 33 is configured to acquire information (for example, a user's instruction) from an input device connected to the server 30 and output information (for example, an image) to an output device connected to the server 30.

[0033] The input device is, for example, a keyboard, a pointing device, a touch panel, or a combination thereof. The output device is, for example, a display.

[0034] The communication interface 34 is configured to control communication between the server 30 and an external device (for example, the client device 10 or the chat server 50).

[0035] (2) One aspect of the embodiment One aspect of this embodiment will be described. FIG. 4 is an explanatory diagram of one aspect of this embodiment.

[0036] As shown in FIG. 4, the information processing system 1 diagnoses an organization composed of a plurality of members ME1. Here, the organization is typically a single company, but according to this embodiment, an organization composed of a plurality of related companies can also be diagnosed. Also, whether the organization has a profit purpose is not a concern.

[0037] The constituent member ME1 is classified into at least one group. The group may be, for example, a department, but may also be a branch, a company, or other organizational unit.

[0038] The constituent member ME1 uses the client device 10 to post messages (which may include posting reactions) to the chat tool and view the messages posted to the chat tool (that is, use the chat tool). In addition to the constituent member ME1, the constituent members of another organization may use the same chat tool as the constituent member ME1. That is, the constituent members of another organization may view the messages posted by the constituent member ME1, or conversely, the constituent member ME1 may view the messages posted by the constituent members of another organization. The usage status data of the chat tool by the constituent member ME1 and the constituent members of another organization (which may be limited to the usage status data related to the organization to be diagnosed) is accumulated in the chat server 50.

[0039] The server 30 obtains the usage status data of the chat tool by the constituent member ME1 and the constituent members of other organizations from the chat server 50. As an example, the server 30 may obtain data such as the poster, posting date and time, destination (for example, the mentioned participant), and thread of the messages posted to the channel as the usage status data of the channel in which the constituent member ME1 participates. The server 30 may obtain the content data of the message as part of the usage status data, or may exclude it from the acquisition target. By excluding the content data of the message from the acquisition target, even if the message contains highly confidential information, the organization can be diagnosed without the risk of leakage of the information.

[0040] Based on the obtained usage status, the server 30 analyzes the communication status in the unit period of the analysis unit whose human composition is at least partially different from that of the organization to be diagnosed, from the perspective of the relationship between the constituent members of the organization included in the analysis unit and other persons included in the analysis unit. The details of the analysis unit will be described later. The unit period may be, for example, one week, one month, or a period of other length.

[0041] Based on the analysis result of the communication state, the server 30 diagnoses the characteristics of the organization. The server 30 presents the diagnosis result of the organization's characteristics to, for example, the management layer MA2 of the organization via the client device 10. The management layer MA2 can grasp the current situation of the organization with reference to the diagnostic information and consider actions for organizational improvement.

[0042] As described above, according to this embodiment, based on the communication state via the chat tool between the members and related parties of the organization in the most recent unit period, the characteristics (personality) of the organization can be diagnosed in a low-cost and timely manner.

[0043] (3) Database The database of this embodiment will be described. The following databases are stored in the storage device 31.

[0044] (3-1) User Database The user database of this embodiment will be described. FIG. 5 is a diagram showing the data structure of the user database of this embodiment.

[0045] The user database stores user information. The user information is information about the users of the chat tool. The users of the chat tool include the members of the organization to be diagnosed, and may further include the members of other organizations who participate in the same channel as the said members. The user information may be obtained from the chat server 50, or at least a part of it may be set manually. The server 30 may access the chat server 50 regularly to update the user database.

[0046] As shown in FIG. 5, the user database includes a "user ID" field, a "user name" field, an "affiliated organization" field, and an "affiliated group" field. Each field is associated with each other.

[0047] The "User ID" field stores the user ID. The user ID is information that uniquely identifies a user of the chat tool.

[0048] The "User Name" field stores user name information. The user name information is information regarding the name of the user (hereinafter referred to as the "target user") identified by the corresponding user ID.

[0049] The "Affiliated Organization" field stores affiliated organization information. The affiliated organization information is information regarding the organization to which the target user belongs.

[0050] The "Affiliated Group" field stores affiliated group information. The affiliated group information is information regarding the group to which the target user belongs. The affiliated group information may change due to transfers within the target user's organization.

[0051] (3-2) Channel Database The channel database of this embodiment will be described. FIG. 6 is a diagram showing the data structure of the channel database of this embodiment.

[0052] The channel database stores channel information. The channel information is information regarding the channels of the chat tool (channels in which members of the organization under diagnosis participate). The channel information may be obtained from the chat server 50, or at least a part thereof may be set manually. The server 30 may periodically access the chat server 50 and update the channel database.

[0053] A channel is a unit for posting and viewing messages in a chat tool, and may be called by different names depending on the specifications of the chat tool. Users who are not participating in a channel are prohibited from posting messages to that channel, and may be prohibited or restricted from viewing messages posted to that channel. A channel that only members belonging to a specific group of an organization can participate in reflects the communication status of that group. A channel that members belonging to different groups of an organization participate in reflects the communication status between those different groups. A channel that members of an organization and members of another organization participate in reflects the communication status between the different organizations.

[0054] As shown in FIG. 6, the channel database includes a "Channel ID" field, a "Reference Destination" field, and a "Participant Affiliation" field. Each field is associated with each other.

[0055] The "Channel ID" field stores the channel ID. The user ID is information that uniquely identifies a channel of the chat tool.

[0056] The "Reference Destination" field stores reference destination information. The reference destination information is information regarding a reference destination (e.g., a URL (Uniform Resource Locator)) for accessing a channel (hereinafter referred to as the "target channel") identified by the corresponding channel ID.

[0057] The "Participant Affiliation" field stores participant affiliation information. The participant affiliation information is information regarding the organization and group to which the participants in the target channel belong. The participant affiliation information may change due to changes in the participants in the target channel (joining or leaving the channel), or due to transfers within the organization of the participants.

[0058] (4) Information Processing The information processing of this embodiment will be described.

[0059] (4-1) Tissue diagnosis process The tissue diagnosis process of this embodiment will be described. FIG. 7 is a flowchart of the tissue diagnosis process of this embodiment. FIG. 8 is a diagram showing an example of a screen displayed in the tissue diagnosis process of this embodiment. FIG. 9 is a diagram showing an example of a screen displayed in the tissue diagnosis process of this embodiment.

[0060] The server 30 can execute the tissue diagnosis process, for example, periodically or in response to a request from a user having the authority to view the diagnosis result.

[0061] As shown in FIG. 7, the server 30 executes the selection of the analysis target channel (S130). Specifically, the server 30 selects the channels necessary for tissue diagnosis. The server 30 selects the channels necessary for tissue diagnosis according to the tissue to be diagnosed and the diagnosis items. As a first example of the selection of the analysis target channel (S130), the server 30 selects, as the analysis target channel, the channel in which the members of the organization to be diagnosed participate. As a second example of the selection of the analysis target channel (S130), the server 30 selects, as the analysis target channel, the channel in which the members belonging to a specific group among the organization to be diagnosed participate. As a third example of the selection of the analysis target channel (S130), the server 30 selects, as the analysis target channel, the channel in which the members belonging to a specific group and the members belonging to another group among the organization to be diagnosed participate. As a fourth example of the selection of the analysis target channel (S130), the server 30 selects, as the analysis target channel, the channel in which the members of the organization to be diagnosed and the members of another organization participate.

[0062] After step S130, the server 30 executes the acquisition of usage data (S131). Specifically, the server 30 acquires the usage data of the analysis target channel selected in step S130 from the chat server 50. As an example, the server 30 can acquire the following data regarding each message posted within a unit period in the analysis target channel as the usage data. · Destination (mention) of the message · Reaction to the message Here, the reaction may include a stamp or a reply. The unit period may be defined differently depending on the diagnostic item, or may be defined uniformly regardless of the diagnostic item.

[0063] Furthermore, the server 30 may, as an option, acquire, as usage status data, data of the message body (for example, the message text, attached file, or file at the link destination described in the message) posted within the unit period in the analysis target channel.

[0064] After step S131, the server 30 executes analysis of the communication state (S132). Specifically, the server 30 analyzes the communication state in the unit period of the analysis unit based on the usage status data acquired in step S131. The analysis unit varies depending on the diagnostic item.

[0065] In the first example of the analysis of the communication state (S132), the server 30 analyzes the communication state in the unit period of the channel of the chat tool associated with the group (hereinafter referred to as the "first channel") for each group included in the organization to be diagnosed. The channel associated with the group is a channel in which only the members belonging to the group can participate. For example, the server 30 calculates a statistical value (representative value or dispersion degree) of the feature amount regarding the message posted to the first channel in the unit period.

[0066] The feature amount regarding the message can include at least one of the following. · Number of posted messages (number or total number for each participant) · Number of destinations (mentions) specified in the message (number or total number for each participant) · Number specified for the destination (mention) in the message (number or total number for each participant) · Number of reactions to a message (number per participant or total number) · Number of times a message has been reacted to (number per participant or total number)

[0067] In the second example of the communication state analysis (S132), the server 30 analyzes the communication state in a unit period of a channel of a chat tool (hereinafter referred to as the "second channel") associated with each combination of different groups included in the organization to be diagnosed. The channel associated with the combination of different groups is a channel in which only the members belonging to each group constituting the combination participate. For example, the server 30 calculates a statistical value (representative value or dispersion degree) of feature quantities regarding the messages posted to the second channel in a unit period.

[0068] In the third example of the communication state analysis (S132), the server 30 analyzes the communication state in a unit period of a channel of a chat tool (hereinafter referred to as the "third channel") associated with each combination of the organization to be diagnosed and another organization. The channel associated with the combination of the organization to be diagnosed and another organization is a channel in which only the members of the organization to be diagnosed and the members of another organization participate. For example, the server 30 calculates a statistical value (representative value or dispersion degree) of feature quantities regarding the messages posted to the third channel in a unit period.

[0069] In the fourth example of the communication state analysis (S132), the server 30 identifies a community corresponding to a conversation cluster based on usage status data and analyzes the communication state in a unit period of the community. As an example, the server 30 creates a network among participants based on whether or not a message specifying a destination (mention) has been posted in a unit period. Each node corresponds to a participant. When a message specifying another participant as the destination (mention) is posted by a certain participant within the unit period, a link is established between the nodes corresponding to the participants.

[0070] The fifth example of the communication state analysis (S132) is a combination of a plurality of the first to fourth examples above.

[0071] After step S132, the server 30 executes a diagnosis of the characteristics of the organization (S133). Specifically, the server 30 diagnoses the characteristics of the organization based on the analysis result of the communication state in step S132.

[0072] In the first example of the diagnosis of the characteristics of the organization (S133), the server 30 calculates a score regarding the trust (hereinafter referred to as "intra-group score") that the members belonging to the group corresponding to the first channel feel towards the people belonging to the group based on the analysis result of the communication state in the unit period of the aforementioned first channel.

[0073] Here, the definition of "trust" in this specification will be explained. The definition as a constituent concept of "trust" is the sense of trust towards others in economic activities. Specifically, the expectation based on the evaluation of the "intention" and "ability" of others is the sense of trust. In particular, the sense of trust in a situation where there is a risk (hazard x probability) that others can betray the expectation is called trust. The actions indicating "trust" in economic activities are, for example, the act of actively disclosing one's own information or the act of transferring the discretion of the work that generates responsibility for oneself to others. In the former case, there is a certain probability of the risk that the other party will not disclose information after self-disclosure. In the latter example, there is a certain probability of the risk that the other party to whom the discretion is transferred cannot achieve the work and one has to take responsibility afterwards. Even in such a situation with such risks, when one evaluates the "intention" and "ability" of others and takes actions indicating trust, it is called "trusting". The operational definition of "trust" is, as an example, a score calculated from the answers of a psychological scale (questionnaire) created based on the above constituent concepts, but in this specification, it may also be a result predicted based on the statistical causal relationship or correlation between the communication state and the score.

[0074] In the second example of the diagnosis of the characteristics of the organization (S133), based on the analysis result of the communication state in the unit period of the aforementioned second channel, the server 30 calculates a score regarding the trust felt by the members belonging to the first group corresponding to the second channel towards the person belonging to the second group corresponding to the second channel (hereinafter referred to as the "inter-group score").

[0075] In the third example of the diagnosis of the characteristics of the organization (S133), based on the analysis result of the communication state in the unit period of the aforementioned third channel, the server 30 calculates a score regarding the trust felt by the members of the organization towards the person belonging to another organization corresponding to the third channel (hereinafter referred to as the "inter-organization score").

[0076] In the first to third examples of the diagnosis of the characteristics of the organization (S133), the server 30 may predict the score using a learned model that has learned the correlation between the feature quantity (explanatory variable) regarding the message and the score (objective variable). The score used for learning can be measured by another method such as a questionnaire survey for the members of the organization. Also, in the first to third examples of the diagnosis of the characteristics of the organization (S133), the server 30 may statistically convert the scores into one score for each group or organization, or may use the scores for each member as the diagnosis result as they are.

[0077] In the fourth example of the diagnosis of the characteristics of the organization (S133), the server 30 calculates an index regarding the openness of the community. As an example, the server 30 calculates, for each member of the organization, the strength of the connection between the member and other members in the community (for example, the number of channels to which a message addressed to the other member from one member is posted). Then, the server 30 sorts the calculated strengths of the connections with other members in descending order to generate a strength distribution and compares it with a reference distribution. The reference distribution is, for example, a Zipf distribution. The server 30 can generate an index indicating that the higher the deviation of the strength distribution from the reference distribution, in other words, the closer it is to a uniform distribution, the higher the openness of the community.

[0078] In the fifth example of the diagnosis of organizational characteristics (S133), the server 30 calculates an index related to the fluidity of the community. As an example, the server 30 compares the temporal changes in the composition of the community (such as the members included in the community, the hub persons, and statistical values of the strength of connections with other members) in different unit periods going back in time. The server 30 may generate an index indicating that the greater the temporal change in the composition of the community, the higher the fluidity of the community.

[0079] In the sixth example of the diagnosis of organizational characteristics (S133), the server 30 identifies the person who becomes the hub of the community. For example, similar to the fourth example described above, for each member of the organization, the server 30 calculates the strength of the connection between the member and other members in the community. Then, the member with the highest strength of connection with other members can be identified as the person who becomes the hub of the community.

[0080] In the seventh example of the diagnosis of organizational characteristics (S133), the server 30 identifies the leader of at least one channel of the chat tool and calculates the degree to which the leader encourages the speech of other participants in the channel. As an example, the server 30 identifies as the leader the participant who posts the most messages to the channel in a unit period. Then, the server 30 calculates the statistical value of the number of designated destinations (mentions) in the messages posted by the leader.

[0081] The eighth example of the diagnosis of the characteristics of the organization (S133) is a combination of a plurality of the above first to seventh examples. For example, when combining a plurality of the above first to third examples, the server 30 may generate information that can compare a plurality of different scores with each other. For example, the server 30 compares a plurality of different scores (for example, determination of magnitude, calculation of difference, or calculation of ratio), and generates a comparison result as a diagnosis result. Alternatively, the server 30 may include the plurality of different scores themselves in the diagnosis result. For example, the server 30 may generate a map image described later. As another example, the server 30 may generate information that can compare a plurality of different scores with respective reference values. The reference value may be, for example, a corresponding score or its representative value in another organization in the same industry as the organization to be diagnosed, or a corresponding score or its representative value in another group in the organization to be diagnosed, or a past score or its representative value in the organization to be diagnosed. For example, the server 30 compares a plurality of different scores with respective reference values (for example, determination of magnitude, calculation of difference, or calculation of ratio), and generates a comparison result as a diagnosis result. Alternatively, the server 30 may include a combination of a plurality of different scores and their respective reference values in the diagnosis result. As yet another example, the server 30 determines an organization type that matches the organization to be diagnosed among a plurality of organization types based on a combination of a plurality of diagnosis results among the above first to seventh examples. The organization type represents a type defined based on a tendency analysis of the characteristics (especially psychological characteristics) of the members of the organization. For example, a combination of a plurality of diagnosis results is defined for each organization type, and the server 30 may search for the organization type that is closest to the combination of diagnosis results by a plurality of the above first to seventh examples. The server 30 generates information indicating the organization type determined to match the organization to be diagnosed as a diagnosis result.

[0082] After step S133, the server 30 executes the output of the diagnosis result (S134). Specifically, the server 30 transmits the diagnosis result of the characteristics of the tissue in step S133 to the client device 10. The client device 10 receives the diagnosis result and presents the diagnosis result to the user. For example, the client device 10 outputs an image or voice based on the diagnosis result from the display 21 or the speaker. The diagnosis result may include data of the image or voice itself, or may include data for generating the image or voice.

[0083] As a first example of the output of the diagnosis result (S134), the server 30 outputs a diagnosis result regarding the score calculated in at least one of the first to third examples of the diagnosis of the characteristics of the tissue (S133). As an example, the client device 10 may display the screen of FIG. 8 on the display 21. The screen of FIG. 8 includes objects J21 to J23.

[0084] The object J21 displays a map image. The map image is an example of information that enables comparison of a plurality of different scores. The map image includes an object J21a, objects J21b1 to J21b3, and objects J21c1 to J21c3.

[0085] The object J21a is an element corresponding to the reference point of the map image. The object J21b1 represents the in-group score together with the object J21c1. The object J21b2 represents the inter-group score together with the object J21c2. The object J21b3 represents the inter-tissue score together with the object J21c3.

[0086] The object J21c1 represents the distance between the object J21a and the object J21b1, and the distance corresponds to the in-group score. As an example, the distance between the object J21a and the object J21b1 may be determined to decrease (for example, be inversely proportional) with an increase in the in-group score.

[0087] Object J21c2 represents the distance between object J21a and object J21b2, and this distance corresponds to the inter-group score. As an example, the distance between object J21a and object J21b2 can be defined to decrease (e.g., be inversely proportional) with an increase in the inter-group score.

[0088] Object J21c3 represents the distance between object J21a and object J21b3, and this distance corresponds to the inter-organization score. As an example, the distance between object J21a and object J21b3 can be defined to decrease (e.g., be inversely proportional) with an increase in the inter-organization score.

[0089] Note that the map image may be prepared for each group or one may be prepared for each organization based on the representative score of the entire organization.

[0090] Object J22 displays the intra-group score, the inter-group score, and the inter-organization score. Further, object J22 displays information indicating the difference from the reference value of each score (an example of information that can compare the score and the reference value). Note that object J22 may display the score for each group or the representative score of the entire organization.

[0091] Object J23 displays a text corresponding to the diagnostic result of the organization based on the score. This text can include information indicating the tissue type determined (based on the score) to be suitable for the tissue to be diagnosed.

[0092] As a second example of the output of the diagnostic result (S133), the server 30 outputs the diagnostic result based on at least one of the fourth to sixth examples of the diagnosis of the characteristics of the organization (S133). As an example, the client device 10 may display the screen of FIG. 9 on the display 21. The screen of FIG. 9 includes objects J24 to J26.

[0093] Object J24 displays the structure of the community. For example, Object J24 displays a network diagram of the community. Object J25 displays information indicating the person who becomes the hub of the community.

[0094] Object J26 displays an index related to the openness of the community. Further, Object J26 may display information that can compare the aforementioned intensity distribution and the reference distribution.

[0095] As a third example of the output of the diagnosis result (S134), the server 30 outputs the result of the analysis in step S132 (for example, information indicating the first channel, the second channel, the third channel, or the identified community (network), or feature amounts related to the message) as the diagnosis result.

[0096] A fourth example of the output of the diagnosis result (S134) is a combination of a plurality of the first to third examples.

[0097] (5) Parentheses As described above, the server 30 of the present embodiment acquires usage status data of the chat tool by the members of the organization, and based on the usage status data, analyzes the communication status in the unit period of the analysis unit whose human composition is at least partially different from that of the organization from the perspective of the relationship between the members of the organization included in the analysis unit and other persons included in the analysis unit. The server 30 diagnoses the characteristics of the organization based on the analysis result of the communication status and outputs the diagnosis result of the characteristics of the organization. Thereby, based on the communication status via the chat tool between the members of the organization and the related parties in the most recent unit period, the characteristics (personality) of the organization can be diagnosed at low cost and in a timely manner.

[0098] The organization may include one or more groups. The server 30 may analyze the communication state in the unit period of the first channel of the chat tool associated with each group included in the organization. Thereby, the characteristics of the organization can be diagnosed based on the communication state among the members of the same group.

[0099] Based on the analysis result of the communication state in the unit period of the first channel, the server 30 may calculate a score regarding the trust that the members belonging to the group corresponding to the first channel feel towards the people belonging to the group. Thereby, the characteristics of the organization can be diagnosed from the perspective of the trust that the members of the same group feel towards each other.

[0100] The organization may include a plurality of groups. The server 30 may analyze the communication state in the unit period of the second channel of the chat tool associated with each combination of different groups included in the organization. Thereby, the characteristics of the organization can be diagnosed based on the communication state among the members of different groups.

[0101] Based on the analysis result of the communication state in the unit period of the second channel, the server 30 may calculate a score regarding the trust that the members belonging to the first group corresponding to the second channel feel towards the people belonging to the second group corresponding to the second channel. Thereby, the characteristics of the organization can be diagnosed from the perspective of the trust that the members of one group feel towards the members of the other group.

[0102] The server 30 may analyze the communication state in the unit period of the third channel of the chat tool associated with each combination of the organization and another organization. Thereby, the characteristics of the organization to be diagnosed can be diagnosed based on the communication state among the members of different organizations including the organization to be diagnosed.

[0103] Based on the analysis result of the communication state in the unit period of the third channel, the server 30 may calculate a score regarding the trust felt by the members of the organization towards a person belonging to another organization corresponding to the third channel. Thereby, from the perspective of the trust felt by the members of the organization to be diagnosed towards the members of another organization, the characteristics of the organization to be diagnosed can be diagnosed.

[0104] Based on the usage data, the server 30 may identify a community corresponding to a conversation cluster and analyze the communication state in the unit period of the community. Thereby, based on the communication state among the members belonging to a dynamic community determined by the presence or absence and intensity of communication rather than a group in the organizational structure, the characteristics of the organization can be diagnosed.

[0105] Based on the analysis result of the communication state in the unit period of the community, the server 30 may calculate an index regarding the openness or fluidity of the community. Thereby, from the perspective of the characteristics (personality) of the community in the organization, the characteristics of the organization can be diagnosed.

[0106] Based on the analysis result of the communication state in the unit period of the community, the server 30 may identify the person who becomes the hub of the community. Thereby, the central figure of the community in the organization can be grasped.

[0107] The server 30 may identify the leader of at least one channel of the chat tool and calculate the degree to which the leader encourages the speech of other participants in the channel. Thereby, from the perspective of the quality of communication in each channel, the characteristics of the organization can be diagnosed.

[0108] (6) Other variations The memory device 11 may be connected to the client device 10 via the network NW. The display 21 may be integrated with the client device 10. The memory device 31 may be connected to the server 30 via the network NW.

[0109] In the above description, examples were shown in which each step is executed in a specific order in each process. However, the execution order of each step is not limited to the examples described as long as there is no dependency. For example, the selection of the analysis target channel (S130) and the acquisition of usage status data (S131) described above may be performed in the reverse order of FIG. 7. That is, the server 30 may first acquire the available usage status data and then select the analysis target channel. Also, the process described as being performed by one device may be performed by another device, or the process described as being performed by the exchange between a plurality of devices may be performed by a single device. For example, each step of the above information processing can be executed by either the client device 10 or the server 30.

[0110] This embodiment can also be used to measure the effect of an event related to an organization. That is, the server 30 may compare, for example, how the characteristics (diagnosis results) of an organization have changed due to events such as education and social gatherings. Specifically, the server 30 receives the designation of an event and compares the diagnosis results before and after the event. Further, the server 30 may compare the diagnosis results by distinguishing between the members who participated in the event and the members who did not participate in the event. Thereby, the influence of an event related to an organization on organizational improvement can be evaluated.

[0111] In the above description, an example was shown in which trust is calculated (predicted) based on the communication state. However, in this embodiment, in addition to or instead of trust, other psychological scales may be calculated (predicted) based on the communication state. Other psychological scales can include, for example, at least one of the following. · Work engagement · Psychological safety · Subjectivity ·Self-discipline ·Regulatory focus of motivation

[0112] As described above in detail regarding the embodiments of the present invention, the scope of the present invention is not limited to the above embodiments. Also, the above embodiments can be variously improved and modified without departing from the gist of the present invention. Further, the above embodiments and modifications can be combined with each other.

Explanation of reference numerals

[0113] 1: Information processing system 10: Client device 11: Storage device 12: Processor 13: Input / output interface 14: Communication interface 21: Display 30: Server 31: Storage device 32: Processor 33: Input / output interface 34: Communication interface 50: Chat server

Claims

1. A computer, means for obtaining usage data of a chat tool by members of an organization, means for analyzing, from the perspective of the relationship between the members of the organization included in the analysis unit and other persons included in the analysis unit, the communication state in a unit period of the analysis unit whose human composition is at least partially different from that of the organization based on the usage data, means for diagnosing the characteristics of the organization based on the analysis result of the communication state, means for outputting the diagnosis result of the characteristics of the organization, A program that functions as such.

2. The organization includes one or more groups, The analyzing means analyzes, for each group included in the organization, the communication state in the unit period of the first channel of the chat tool associated with the group, The program according to claim 1.

3. The diagnosing means calculates a score regarding the trust felt by the members belonging to the group corresponding to the first channel towards the persons belonging to the group based on the analysis result of the communication state in the unit period of the first channel, The program according to claim 2.

4. The organization includes a plurality of groups, The analyzing means analyzes, for each combination of different groups included in the organization, the communication state in the unit period of the second channel of the chat tool associated with the combination, The program according to claim 1.

5. The means for diagnosing calculates a score regarding the trust felt by a member belonging to a first group corresponding to the second channel toward a person belonging to a second group corresponding to the second channel, based on the analysis result of the communication state in the unit period of the second channel. The program according to claim 4.

6. The means for analyzing analyzes the communication state in the unit period of a third channel of the chat tool associated with the combination, for each combination of the organization and another organization. The program according to claim 1.

7. The means for diagnosing calculates a score regarding the trust felt by a member of the organization toward a person belonging to the other organization corresponding to the third channel, based on the analysis result of the communication state in the unit period of the third channel. The program according to claim 6.

8. The means for analyzing identifies a community corresponding to a conversation cluster based on the usage status data, and analyzes the communication state in the unit period of the community. The program according to claim 1.

9. The means for diagnosing calculates an index regarding the openness or the fluidity of the community, based on the analysis result of the communication state in the unit period of the community. The program according to claim 8.

10. The means for diagnosing identifies a person who becomes a hub of the community, based on the analysis result of the communication state in the unit period of the community. The program according to claim 8.

11. The means for diagnosis identifies at least one leader of a channel of the chat tool and calculates the degree to which the leader promotes the speech of other participants in the channel. The program according to claim 1.

12. Function the computer as means for receiving a designation of an event related to the organization. The means for diagnosis compares changes in the diagnosis results before and after the event. The program according to claim 1.

13. The means for diagnosis compares the diagnosis results between the members of the organization who participated in the event and the members of the organization who did not participate in the event. The program according to claim 12.

14. Means for obtaining usage status data of a chat tool by members of an organization, Based on the usage status data, analyze the communication state in a unit period of an analysis unit whose human composition is at least partially different from that of the organization, from the perspective of the relationship between the members of the organization included in the analysis unit and other persons included in the analysis unit. Means for diagnosing the characteristics of the organization based on the analysis result of the communication state, Means for outputting the diagnosis result of the characteristics of the organization An information processing apparatus comprising:

15. The computer Performs the steps of obtaining usage status data of a chat tool by members of an organization, Based on the usage status data, analyze the communication state in a unit period of an analysis unit whose human composition is at least partially different from that of the organization, from the perspective of the relationship between the members of the organization included in the analysis unit and other persons included in the analysis unit. Based on the analysis result of the communication state, perform the step of diagnosing the characteristics of the organization. A step of outputting a diagnosis result of the characteristics of the organization and a method of executing the same.

16. A system including a plurality of information processing devices, means for obtaining usage status data of a chat tool by members of an organization, means for analyzing, from the perspective of the relationship between the members of the organization included in the analysis unit and other persons included in the analysis unit, the communication state in a unit period of the analysis unit whose human composition is at least partially different from that of the organization based on the usage status data, means for diagnosing the characteristics of the organization based on the analysis result of the communication state, and means for outputting a diagnosis result of the characteristics of the organization and a system comprising the same.

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