JP7701037B2 - Status analysis device, recommended activity information proposal support device, status analysis method, recommended activity information proposal support method, program, and recording medium - Google Patents

Description

The present invention relates to a status analysis device, a recommended activity information proposal support device, a status analysis method, a recommended activity information proposal support method, a program, and a recording medium.

It is generally said that Japanese people are not good at directly expressing gratitude to others. On the other hand, it has also been reported that in companies and other organizations, expressing gratitude to others has a positive effect on performance.

For example, Patent Document 1 proposes a system for building trust between members of an organization through a computer network.

JP 2006-40253 A

In organizations made up of multiple members, there is a demand for technology that can grasp the status of the organization and its members.

The present invention aims to provide a status analysis device, a status analysis method, a program, and a recording medium that can grasp the status of an organization and the status of the members of the organization.

In order to achieve the above object, the status analysis device of the present invention includes a gratitude data acquisition unit, a network generation unit, a network feature amount analysis unit, an organization status identification unit, a member status analysis unit, and an output unit,
the thank you data acquisition unit acquires thank you data transmission history information indicating that thank you data has been transmitted from one member to another member;
The network generation unit generates a member network within an organization to which the member belongs based on the gratitude data transmission history information,
The network feature analysis unit analyzes features of the member network,
The organizational state identification unit identifies an organizational state based on the feature amount of the analyzed member network,
The member status analysis unit analyzes the status of the member based on the feature amount of the member network,
The output unit outputs the organizational status and the member status.

The status analysis method of the present invention includes a gratitude data acquisition step, a network generation step, a network feature analysis step, an organization status identification step, a member status analysis step, and an output step.
The thank you data acquisition step acquires thank you data transmission history information indicating that thank you data has been transmitted from one member to another member,
The network generating step generates a member network within an organization to which the member belongs based on the gratitude data transmission history information,
The network feature analysis step includes analyzing a feature of the member network,
The organizational state identification step includes identifying an organizational state based on the feature amount of the analyzed member network,
The member status analysis step includes analyzing the status of the member based on a feature amount of the member network,
The output step outputs the organizational status and the member status.

A first program of the present invention is a program for causing a computer to execute a procedure for acquiring gratitude data, a procedure for generating a network, a procedure for analyzing network features, a procedure for identifying an organization state, a procedure for analyzing a member state, and a procedure for outputting the data,
The thank you data acquisition step acquires thank you data transmission history information indicating that thank you data has been transmitted from one member to another member;
The network generation step generates a member network within an organization to which the member belongs based on the gratitude data transmission history information;
The network feature analysis step includes analyzing a feature of the member network,
The organizational state identification step includes identifying an organizational state based on the feature amount of the analyzed member network;
The member status analysis step includes analyzing the status of the member based on a feature amount of the member network,
The output procedure is a program that outputs the organization status and the member status.

The present invention makes it possible to understand the state of an organization and the state of its members.

FIG. 1 is a block diagram showing an example of a configuration of an apparatus according to the first embodiment. FIG. 2 is a block diagram illustrating an example of a hardware configuration of the apparatus according to the first embodiment. FIG. 3 is a flowchart showing an example of processing in the device of the first embodiment. FIG. 4 is a diagram showing an example of thank-you data transmission history information. FIG. 5 is a diagram showing an example of the generated member network. FIG. 6 is a diagram showing an example of analyzing the feature quantities of a member network. FIG. 7 is a diagram showing an example of calculation of betweenness centrality. FIG. 8 illustrates an example of calculation of the number of complete graphs. FIG. 9 is a diagram showing an example of calculation of the average shortest distance. 10A and 10B are schematic diagrams showing an example of a member network, and FIG. 10C is a schematic diagram showing an example of an analysis of the member status. FIG. 11 is a block diagram illustrating an example of a configuration of an apparatus according to the second embodiment. FIG. 12 is a flowchart showing an example of processing in the device of the second embodiment. FIG. 13 is a schematic diagram of a display unit in the device of the second embodiment. FIG. 14 is a schematic diagram of a display unit in the device of the second embodiment. FIG. 15 is a schematic diagram of a display unit in the device of the second embodiment. FIG. 16 is a schematic diagram of a display unit in the device of the second embodiment. FIG. 17 is a schematic diagram of a display unit in the device of the second embodiment. FIG. 18 is a schematic diagram of a display unit in the device of the second embodiment. FIG. 19 is a block diagram illustrating an example of a configuration of an apparatus according to the third embodiment. FIG. 20 is a block diagram illustrating an example of a hardware configuration of an apparatus according to the third embodiment. FIG. 21 is a flowchart showing an example of processing in the device of the third embodiment. FIG. 22 is a table showing an example of recommended activity information and recommendation scores linked to combinations of organization states and member states. FIG. 23 is a block diagram showing an example of the configuration of an apparatus according to the fourth embodiment. FIG. 24 is a flowchart showing an example of processing in the device of the fourth embodiment. FIG. 25 is a table illustrating an example of activity information. FIG. 26 is a table showing an example of updating the recommendation score.

In the present invention, "member" means a member of an organization, and the organization is not particularly limited, and examples include organizations that are composed of multiple members. Specific examples of the members include employees, union members, staff, medical professionals, athletes, members, students, etc. Furthermore, examples of the organizations include companies, unions, government agencies, hospitals, sports teams, clubs, schools, etc.

Next, an embodiment of the present invention will be described with reference to the drawings. The present invention is not limited to the following embodiment. In each of the drawings, the same parts are given the same reference numerals. Furthermore, the explanations of each embodiment can be mutually incorporated unless otherwise specified, and the configurations of each embodiment can be combined unless otherwise specified.

[Embodiment 1]
FIG. 1 is a block diagram showing an example of the configuration of a state identification device 10 according to the present embodiment. As shown in FIG. 1, the device 10 includes a gratitude data acquisition unit 11, a network generation unit 12, a network feature analysis unit 13, an organization state identification unit 14, a member state analysis unit 15, and an output unit 16. Although not shown, the state analysis device 10 may be connected to a database outside the device via a communication line network. In addition, although not shown, the state analysis device 10 may also be connected to an external terminal of a system administrator via a communication line network, for example, and the system administrator may manage the state analysis device 10 from the external terminal.

The device 10 may be, for example, a single device including each of the above-mentioned parts, or a device to which each of the above-mentioned parts can be connected via a communication line network. The device 10 can also be connected to an external device described later via a communication line network. The communication line network is not particularly limited, and any known network can be used, for example, wired or wireless. Examples of communication line networks include the Internet line, WWW (World Wide Web), telephone line, LAN (Local Area Network), SAN (Storage Area Network), DTN (Delay Tolerant Networking), LPWA (Low Power Wide Area), L5G (Local 5G), etc. Examples of wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), local 5G, and LPWA. The wireless communication may be a form in which each device communicates directly (Ad Hoc communication), infrastructure communication, indirect communication via an access point, and the like. The device 10 may be incorporated into a server as a system. The device 10 may be, for example, a personal computer (PC, for example, desktop type or notebook type) in which the program of the present invention is installed, a smartphone, a tablet terminal, or the like. Furthermore, the device 10 may be in the form of cloud computing or edge computing, for example, in which at least one of the parts is on a server and the other parts are on a terminal.

Figure 2 shows an example block diagram of the hardware configuration of the device 10. The device 10 includes, for example, a CPU 101, a memory 102, a bus 103, a storage device 104, an input device 106, a display device (display) 107, and a communication device 108. Each part of the device 10 is connected to each other via the bus 103 by its respective interface (I/F).

The CPU 101, for example, works in conjunction with other components via a controller (system controller, I/O controller, etc.) and is responsible for overall control of the device 10. In the device 10, the CPU 101 executes, for example, the program 105 of the present invention and other programs, and also reads and writes various information. Specifically, for example, the CPU 101 functions as a gratitude data acquisition unit 11, a network generation unit 12, a network feature analysis unit 13, an organization state identification unit 14, a member state analysis unit 15, and an output unit 16.

The bus 103 can also be connected to, for example, an external device. Examples of the external device include an external storage device (external database, etc.), a printer, an external input device, an external display device, and an external imaging device. The device 10 can be connected to an external network (the communication line network) by, for example, a communication device 108 connected to the bus 103, and can also be connected to other devices via the external network.

The memory 102 may be, for example, a main memory (primary storage device). When the CPU 101 performs processing, the memory 102 reads various operating programs, such as the program 105 of the present invention stored in the storage device 104 described below, and the CPU 101 receives data from the memory 102 and executes the program. The main memory may be, for example, a RAM (random access memory). The memory 102 may also be, for example, a ROM (read only memory).

The storage device 104 is also called an auxiliary storage device, for example, in contrast to the main memory. As described above, the storage device 104 stores the operating program 105 including the program of the present invention. The storage device 104 may be, for example, a combination of a recording medium and a drive that reads and writes from the recording medium. The recording medium is not particularly limited, and may be, for example, an internal or external type, and may be a hard disk (HDD), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, memory card, etc. The storage device 104 may be, for example, a hard disk drive (HDD) in which the recording medium and the drive are integrated, and a solid state drive (SSD). When the device 10 includes, for example, the storage unit, the storage device 104 functions as the storage unit.

In the present device 10, the memory 102 and storage device 104 can also store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the present device 10, and information used by the present device 10 when executing processing. Note that at least a portion of the information may be stored, for example, in an external server other than the memory 102 and storage device 104, or may be stored in a distributed manner across multiple terminals using blockchain technology or the like.

The device 10 further includes, for example, an input device 106 and a display 107. Examples of the input device 106 include pointing devices such as a touch panel, track pad, and mouse; a keyboard; imaging means such as a camera and scanner; card readers such as an IC card reader and a magnetic card reader; and audio input means such as a microphone. Examples of the display 107 include display devices such as an LED display and a liquid crystal display. In the first embodiment, the input device 106 and the display 107 are configured separately, but the input device 106 and the display 107 may be configured as one unit, such as a touch panel display.

Next, an example of the condition analysis method of this embodiment will be described based on the flowchart in FIG. 3. The condition analysis method of this embodiment is carried out as follows, for example, using the condition analysis device 10 shown in FIGS. 1 and 2. Note that the condition analysis method of this embodiment is not limited to the use of the condition analysis device 10 shown in FIGS. 1 and 2.

First, the gratitude data acquisition unit 11 acquires gratitude data transmission history information indicating that one member has sent gratitude data to another member (S1, gratitude data acquisition process). The gratitude data may be, for example, data expressing gratitude, and may include, for example, the type of gratitude (for example, "thank you," "sorry," "praise," "respect," "happy," etc.), the degree of gratitude, and a comment on gratitude. The format of the gratitude data is not particularly limited, and may include, for example, characters, text, and illustrated images. The gratitude data transmission history information may include information such as the date and time of transmission of the gratitude data in addition to information indicating who sent the gratitude data to whom. The gratitude data may further include, for example, attribute information of the person who sent the gratitude and the person who received the gratitude. Examples of the attribute information include, for example, gender, age, and position in the organization (for example, department, position, rank, occupational area, qualification holder, annual income band, etc.). When the gratitude data includes the attribute information, the gratitude data transmission history information may include, for example, attribute information of the one member and attribute information of the other member. The thanks data acquisition unit 11 may acquire, for example, the thanks data itself as the thanks data transmission history information, or may acquire statistical information as described below, or may acquire log information from the terminal transmitting the thanks data. The acquisition format may be, for example, acquisition from a database or server that stores the thanks data via the communication line network, or acquisition from a thanks transmission device (described below) that is the member's terminal (also called a member terminal). Specifically, the transmission of the thanks data from one member to another member will be described in embodiment 3 below. The thanks data transmission history information acquired by the device 10 may be output to an external database or server via the communication line network, or may be stored in a storage unit such as the memory 102 and the storage device 104.

Next, the network generation unit 12 generates a member network within the organization to which the member belongs based on the gratitude data transmission history information (S2, network generation process). The member network is, for example, data showing the relationships (e.g., intimate relationships) between multiple members within the organization, and is also called a correlation diagram. The form of the member network is not particularly limited, and may be, for example, map information in which a line connects one member who transmitted the gratitude data and the other member who received the gratitude data among multiple members. The member network may be, for example, a directed graph or an undirected graph. In addition, for example, when the gratitude data transmission history information includes attribute information of the one member and attribute information of the other member, the network generation unit 12 may generate the member network in which the attribute information of each member is linked.

Next, the network feature analysis unit 13 analyzes the features of the member network (S3, network feature analysis step). The features are not particularly limited, and examples include centrality indices in the member network (betweenness centrality, degree centrality, closeness centrality, eigenvector centrality, etc.), the number of complete graphs, and the average shortest distance. The features to be analyzed may be, for example, one or two or more.

The network feature analysis unit 13 may further determine the network type of the member network from the feature, for example. Examples of the network type include a distributed type, a silo type, a bridge type, and a bonding type. The distributed type member network indicates, for example, an organizational state in which the connections between nodes (members) are weak or there are no connections at all. The silo type member network indicates, for example, an organizational state in which there are multiple smaller organizations within an organization and there are no connections between the smaller organizations. The bridge type member network indicates, for example, an organizational state in which, like the silo type, an organization contains small organizations within itself, but these small organizations are connected to each other. The bonding type member network indicates, for example, an organizational state in which no small organizations are formed within an organization and there are many connections between nodes (members) (i.e., there are many nodes with high degrees). More specifically, this will be described later. This makes it possible to quantitatively express the organizational state described later.

Next, the organizational state identification unit 14 identifies the organizational state based on the features of the analyzed member network (S4, organizational state identification process). The organizational state identification unit 14 may also identify the organizational state based on the network type. The organizational state is not particularly limited, and examples include the formation stage, confusion stage, unification stage, functioning stage, and dissolution stage in the Tuckman model. The formation stage is, for example, a stage in which the members who will belong to the organization are decided and the members are waiting to see what happens to each other. The confusion stage is, for example, a stage in which opinions, principles, and assertions clash and the members are wary of each other. The unification stage is, for example, a stage in which goals are shared by the members and rules to be followed as an organization are established. The functioning stage is, for example, a stage in which each member acts autonomously and produces results. The dissolution stage is, for example, a state in which the organization is dissolved due to the achievement of a goal or time constraints, and each member begins to move toward a different goal. Below, the tissue state will be described using each stage of the Tuchman model, but other models may be used without being limited to this. Specifically, the tissue state identification unit 14 may identify the tissue state into at least four stages (e.g., the formation stage, the disorganization stage, the integration stage, and the function stage, etc.) as described below.

Next, the member status analysis unit 15 analyzes the status of the member based on the feature quantities of the member network (S5, member status analysis step). The status of the member can be, for example, the state of satisfaction of the member with the organization, and can be evaluated using two axes of hygiene factors and motivation factors of the member using Herzberg's two-factor theory. The hygiene factors of the member (also called dissatisfaction factors) can be evaluated, for example, based on the relationship between the member and other members belonging to the organization, that is, the interpersonal satisfaction of the member. The motivation factors can be evaluated, for example, based on the extent to which the member's desire for recognition is satisfied, that is, the member's degree of recognition. The member status analysis unit 15 calculates the member's degree of recognition and interpersonal satisfaction based on, for example, degree centrality among the feature quantities of the analyzed member network. The member status analysis unit 15 can then analyze the member's status into at least four stages based on the recognition degree and interpersonal satisfaction of each member. Examples of the four stages of states include the first quadrant (both approval and interpersonal satisfaction are good), the second quadrant (only interpersonal satisfaction is good), the third quadrant (both approval and interpersonal satisfaction are poor), and the fourth quadrant (only approval is good).

Specifically, the member status analysis unit 15 calculates the interpersonal satisfaction of the member based on the degree centrality between the node (member) to be analyzed and other nodes (other members) in the member network, for example. In addition, in the case where the member network in which the attribute information of each member is linked is generated in S2, the member status analysis unit 15 calculates the approval degree of the member to be analyzed based on the degree centrality between the member to be analyzed and other members having any attribute information. Then, the member status analysis unit 15 compares the approval degree and interpersonal satisfaction of each member in the organization, for example, and analyzes which of the four stages the state of the member to be analyzed belongs to depending on whether the approval degree and interpersonal satisfaction of the member to be analyzed are higher or lower than the average approval degree and the average interpersonal satisfaction of each member in the organization. Note that the member status analysis unit 15 may analyze the state based on whether the approval degree and interpersonal satisfaction of the member to be analyzed are higher or lower than an arbitrary threshold, for example, instead of the average value. Below, we will explain an example of an analysis method that uses Herzberg's two-factor theory to analyze the status of the members, but the present invention is not limited to this, and analysis methods that use other theories may also be used.

Then, the output unit 16 outputs the organizational status and the status of the members (S6, output step). The output by the output unit 16 may be, for example, an output (display) on the display 107 of the device 10, or may be output to an external device via the communication line network. An example of the external device is a terminal of the member.

According to this embodiment, a member network is generated from thank you data transmission history information, and the state of the organization and the state of the members can be understood based on the member network. The transmission history of tools such as email and chat does not make it clear whether the interpersonal relationships between each member are good or not. However, according to this embodiment, since it is based on thank you data transmission history information, it is possible to analyze the state taking into account the interpersonal relationships between each member.

[Embodiment 2]
Specifically, an example of analyzing the state of an organization and the state of its members using the device 10 will be described. In the following, the members will be employees and the organization will be a company, but as mentioned above, this is not limited to this, and in the following description, employees can be read as members and companies can be read as organizations, respectively.

First, an example of understanding the organizational state will be described. Each employee in a company uses, for example, a thanks transmission device described below to send thanks data to other employees in the company. Then, the thanks data acquisition unit 11 of the device 10 acquires the thanks data transmission history information from the thanks transmission device. Figure 4 shows an example of the thanks data transmission history information. In Figure 4, "From" indicates the employee who sent the thanks data, and "Target" indicates the employee to whom the thanks data was sent.

Next, as shown in FIG. 5, the network generation unit 12 reads the gratitude data transmission history information and generates a member network (also called networking). In the member network, the distance and direction between each node (each employee) are not particularly limited, and may or may not be calculated according to the feature amount described below. The distance between each node (each employee) can be, for example, processed as the degree of gratitude in the gratitude data as the distance between nodes. The degree of gratitude will be described later. Hereinafter, in the member network, the employees are also called nodes.

Next, as shown in FIG. 6, the network feature analysis unit 13 analyzes the features of the member network and determines the network type of the member network from the features. In FIG. 6, the features are betweenness centrality, number of complete graphs, and average shortest distance, but as described above, the features are not limited to these. Specifically, the network feature analysis unit 13 determines, for example, a member network in which all betweenness centralities are 0 and the number of complete graphs is 0 as a "distributed type". In addition, the network feature analysis unit 13 determines, for example, a member network in which the top two betweenness centralities are 0.2 or less and the number of complete graphs is 2 or more as a "silo type". In addition, the network feature analysis unit 13 determines, for example, a member network in which the top two betweenness centralities are 0.9 or more and the number of complete graphs is 0 as a "bridge type". In addition, the network feature analysis unit 13 determines, for example, a member network in which the number of complete graphs is 0 and the average shortest distance is 5 to 6 as a "bonding type". These values are merely examples and can be set arbitrarily. The device 10 may store in advance table data showing the relationship between the feature amounts and each network type, as shown in FIG. 6, or may obtain the data from outside via the communication line network.

Then, the organizational state identification unit 14 of the device 10 identifies the state of an organization having the decentralized member network as a "formation stage," the state of an organization having the silo-type member network as a "confusion stage," the state of an organization having the bridge-type member network as a "unification stage," and the state of an organization having the bonding-type member network as a "functional stage."

An example of betweenness centrality calculation will be described with reference to FIG. 7. The betweenness centrality can be calculated, for example, using formula (1) shown in FIG. 7. Specifically, node 1 shown in the lower part of FIG. 7 will be used as an example. The betweenness centrality can be calculated by dividing the number of paths (B) that pass through node 1 among the shortest paths by the number of shortest paths (A) between each node, and finding the sum of the results. In other words, the betweenness centrality of node 1 shown in the lower part of FIG. 7 is 3.5.

An example of the calculation of the number of complete graphs will be described with reference to FIG. 8. A complete graph means that the graph G does not include a self-loop (a closed path consisting of one branch) and has one branch connecting all two distinct points, and a complete graph with n vertices can be expressed as K _n (n is an integer of 1 or more). FIG. 8(A) shows an example of complete graphs K ₁ to K _4. Next, a specific example of the calculation of the number of complete graphs will be described with reference to FIG. 8(B). First, n arbitrary nodes (n is an integer of 1 or more) are extracted from the member network. Then, when the number m (m is an integer of 1 or more) of edges consisting of the extracted n nodes is the same as the number of the extracted nodes, the part of the member network is regarded as a complete graph. Then, the sum of the complete graphs is regarded as the number of complete graphs. Specifically, the member network (1) shown in the lower part of FIG. 8 is obtained by extracting each node surrounded by each frame. In this case, as shown in the figure, the parts of the member network within each frame are both complete graphs (n=3, m=3). On the other hand, the member network (2) is extracted by extracting each node enclosed in a frame. In this case, as shown in the figure, the part of the member network within each frame is not a complete graph (n=2, m=1).

An example of calculating the average shortest distance will be described with reference to FIG. 9. First, any one node is selected from the member network. Hereinafter, the selected node is also referred to as the origin. Next, as shown in the figure, a node adjacent to the origin is set to have Erdős number n. Also, a node that is not adjacent to the origin and has Erdős number n (n is an integer equal to or greater than 1) is set to have Erdős number n+1. On the other hand, a node that does not fit the above criteria is set to have Erdős number ∞. Then, the average shortest distance can be calculated, for example, using formula (2) shown in FIG. 9.

An example of analyzing the status of members will be described with reference to FIG. 10. FIGS. 10(A) and (B) are schematic diagrams showing an example of a member network, and FIG. 10(C) is a schematic diagram showing an example of analyzing the status of members. First, as the interpersonal satisfaction of the member (supervisor) to be analyzed, the degree centrality in the member network is calculated for all nodes connected to the member (chief) as shown in FIG. 10(A). Next, as the approval level of the member (chief), as shown in FIG. 10(B), the degree centrality in the member network is calculated for nodes connected to the member (chief) that are linked to positions higher than chief (department manager and section manager) as the attribute information. Then, the interpersonal satisfaction and approval level are calculated for each member of the organization in the same manner, and compared with the average interpersonal satisfaction and average approval level of the organization to which the member (supervisor) belongs, to determine into which state (quadrant) shown in FIG. 10(C) the member (supervisor) is classified, and the state of the member (supervisor) is analyzed.

[Embodiment 3]
The transmission of the thank-you data from one member to another member will be specifically described. Note that this is an example and is not limiting. The thank-you data can be transmitted from one member to another member by using, for example, the technology described in JP 2018-147494 A (hereinafter, also referred to as a thank-you transmission device).

The transmission of the gratitude data is executed, for example, by the gratitude transmission device 20. FIG. 11 shows an example of the configuration of the gratitude transmission device 20 of the embodiment. The gratitude transmission device 20 includes a memory unit 21, a display unit 22, a selection unit 23, and a transmission/reception unit 24. Furthermore, the gratitude transmission device 20 may further include a statistics unit 25, etc., as an optional configuration. The hardware configuration of the gratitude transmission device 20 is not particularly limited, but is, for example, similar to that of the state identification device 10. Specifically, the CPU 101 functions, for example, as the selection unit 23, the transmission/reception unit 24, and the statistics unit 25, the display unit 22 can use, for example, the display 107, and the memory unit 21 can use the memory 102 or the storage device 104.

The gratitude transmission device 20 is a device owned by each user (i.e., member), and each gratitude transmission device 20 owned by each user may be connectable to each other, for example, via the communication line network.

Next, the gratitude transmission method of this embodiment will be described with reference to Figures 12 to 18. Figure 12 is a flowchart of the gratitude transmission method, and Figures 13 to 18 are schematic diagrams of the display unit 22 of the gratitude transmission device 20. Note that the gratitude transmission method of this embodiment is not limited to use of the gratitude transmission device 20.

(A1) Storage process First, the storage unit 21 stores the thank-you data and the user data of a plurality of users. The thank-you data is as described above. The user data includes, for example, the terminal data of the user, and further includes, for example, identification data for identifying the user (also referred to as specific data for identifying the user). The storage unit 21 stores, as the user data, for example, the identification data of the user and the terminal data in association with each other. The user identification data may be, for example, information that can identify a specific user from a plurality of users, and specific examples include a name, a nickname, a photographic image, an illustrated image, and the like, and may further include affiliation, etc. The terminal data is, for example, data for transmitting and receiving data via the communication line network, and specific examples include an IP address, etc. The number of user data stored in the storage unit 21 is not particularly limited, and can be stored, for example, for members belonging to any organization that conveys gratitude. The plurality of users can be further stored, for example, as a group that invites members to share. Furthermore, the user data of the multiple users may be stored as, for example, an address book.

(A2) User Data Display Process Next, the user identification information of the multiple users is displayed by the display unit 22. Specifically, the display unit 22 displays, for example, names, photographic images, illustration images, etc., as the user identification data for the multiple users. Specifically, as shown in Fig. 13, the display unit 22 of the gratitude transmission device 20 displays user names (e.g., Mr. A, Mr. B, etc.) and photographic images (e.g., face photos) or illustration images (e.g., illustrations of turtles), etc.

(A3) Step of selecting a specific user Next, a specific user is selected from the multiple user identification information displayed by the selection unit 23. When a specific user is selected, as shown in the left diagram of Fig. 14, for example, the specific user (Mr. B) selected as the recipient of the thank-you message is displayed on the display unit 22.

(A4) Display process of multiple types of thanks When a specific user is selected by the selection unit 23, multiple types of thanks are displayed on the display unit 22 as the thanks data in addition to the selected specific user. The types of thanks are not particularly limited, and examples include "thank you,""sorry,""praise,""respect," and "happy." The types of thanks are displayed, for example, as images expressing the types of thanks, and the images may be, for example, only words, only illustrations expressing thanks, or a combination of words and illustrations.

The display unit 22 can display multiple types of thanks simultaneously or sequentially. In the latter case, for example, the display unit 22 can sequentially display the images indicating the multiple types of thanks on the display unit 22 by moving an arbitrary image indicating the type of thanks displayed on the display unit 22 on the display unit 22 by sliding, swiping, or the like. At this time, for example, in order to indicate that an image indicating the type of thanks exists in addition to the arbitrary image displayed on the display unit 22, the display unit 22 may display an arbitrary image indicating the type of thanks and may display a part of another adjacent image indicating the type of thanks to the left and right or above and below the arbitrary image. Specifically, as shown in the left diagram of FIG. 14, the selected specific user (Mr. B) is displayed on the display unit 22, and further, as a type of thanks, the word "Good!", which is a word that evaluates the other person's behavior, and an image of an illustration representing it are displayed in the center of the lower direction. At this time, as shown in the left diagram of FIG. 14, a part of another adjacent image is displayed to the left and right of the image of "Good!". This allows the user to recognize that there are other images to the left and right of the "Good!" image. By sliding the "Good!" image, for example, the "Thank you" image to the right of the "Good!" image can be displayed in the center of the lower part of the display unit 22, as shown in the right diagram of FIG. 14.

(A5) Step of selecting a specific type of thanks Next, a specific type of thanks is selected from the displayed types of thanks by the selection unit 23. When a specific type of thanks is selected, as shown in Fig. 15, for example, an image showing the selected specific user (Mr. B) and the selected type of thanks (Thank you) is displayed on the display unit 22.

(A6) Step of Displaying Multiple Degrees of Gratitude Next, when a specific type of gratitude is selected by the selection unit 23, the display unit 22 displays, for example, the degree of gratitude in addition to the selected type of gratitude. The degree of gratitude can be displayed, for example, by a bar image representing the degree of gratitude. Specifically, as shown in FIG. 15, a five-level bar indicating the degree of gratitude is displayed next to an image showing the type of gratitude (thank you). The bar, for example, represents the degree of gratitude by its height, and the higher the bar is, the stronger the degree of gratitude.

(A7) Selection process of specific degree of gratitude Next, the selection unit 23 selects a specific degree of gratitude from the degrees of gratitude displayed on the display unit 22. When the specific degree of gratitude is selected, as shown in FIG. 15, a bar showing the degree of gratitude in five stages is displayed on the display unit 22. For example, as shown in the left diagram of FIG. 15, when the degree of gratitude is shown in three stages as a provisional standard (the bars from the bottom to the third stage are displayed in black), as shown in the right diagram of FIG. 15, the color of the bar up to the fifth stage can be changed to black to show that the degree of gratitude to B is five stages in a five-stage evaluation. The color of the bar is not particularly limited, and, for example, an evaluation stage can be selected by swiping from the first stage bar to the desired stage bar among the five stages of the bars displayed on the display unit 22.

(A8) Transmission step Then, the transmission/reception unit 24 transmits the selected specific thank you data (for example, the specified type of thank you and the degree of thank you) to the terminal of the selected specific user. Specifically, as shown in the order of Fig. 16 (A) to (C), the "Thank you" image is moved by flicking or dragging toward the image showing the selected specific user (Mr. B) shown on the display unit 22. This allows the thank you data, in which the type of thank you is "Thank you" and the degree of thank you is "on a five-level scale," to be transmitted to the specific user, Mr. B, via the network to the terminal of the specific user.

(A9) Receiving step (not shown)
The method of the present embodiment includes, for example, a step of receiving thank-you data (e.g., a selected specific type of thank-you and a selected specific degree of thank-you) transmitted from another user. The step can be executed, for example, by the transceiver unit 24 and the display unit 22 of the thank-you transmission device 20. The timing of receiving the thank-you data is not particularly limited.

In this embodiment, the order in which the thank you data and the user identification information of the multiple users are displayed on the display unit 22 is not particularly limited. For example, as described above, the thank you data may be displayed after the user identification information is displayed, or both may be displayed simultaneously.

The gratitude transmission method of this embodiment may further include, for example, a storage step of storing the transmitted gratitude data and the received gratitude data as transmission/reception history data, which can be executed, for example, by the storage unit 21 of the gratitude transmission device 20.

In this embodiment, the display unit 22 may further display, for example, a list of part or all of the thank-you data transmitted from the terminal, and a list of part or all of the thank-you data received by the terminal. As shown in FIG. 17, for example, when a transmission list is selected on the display unit 22 of the terminal 20 that is a thank-you transmission device, a list of thank-you data transmitted from the terminal 20 can be displayed. The contents of the thank-you data displayed in the list are, for example, the destination user, the type of thank-you, the degree of thank-you, the transmission time, etc. Also, although not shown, for example, when a reception list is selected on the display unit 22 of the terminal 20 that is a thank-you transmission device, a list of thank-you data received by the terminal 20 can be displayed. The contents of the thank-you data displayed in the list are, for example, the type of thank-you, the degree of thank-you, the transmission time, etc., and the sender user may or may not be displayed, and may not be displayed as anonymity for ease of expressing gratitude.

(A10) Statistical process (not shown)
In this embodiment, the thank-you transmission device 20 may further include, for example, a statistical unit 25, which calculates statistical data based on the transmitted thank-you data and the received thank-you data. In this case, the display unit 22 may further display, for example, the statistical data.

The types of statistical data based on the transmitted and received thanks data by the statistics unit 25 are not particularly limited, and specific examples include the total amount of thanks data transmitted from the terminal, the total amount of thanks data received by the terminal, the ratio between the amount of thanks data transmitted and the amount of thanks data received by the terminal, the change in the amount of thanks data over time, the ratio of types of thanks and the ratio of degrees of thanks in the transmitted and received thanks data, etc. Furthermore, if each terminal (thanks transmission device 20) can be connected to a server as described above, for example, the total amount of thanks data stored in the server for each terminal (thanks transmission device 20) can also be displayed as statistical data. Here, the amount of thanks data is not particularly limited, and can be expressed, for example, as the product of the number (number of times) of thanks data transmitted and received and the degree of thanks.

As shown in FIG. 18, for example, the statistical data can be displayed on the display unit 22 of the terminal 20, which is a gratitude transmission device, in the form of numerical values, pie charts, bar graphs, line graphs, etc., showing the total amount of gratitude from multiple terminals connected via the communication line network, the amount of gratitude sent and received by the terminals, the ratio between the amount of gratitude sent and the amount of gratitude received (e.g., over the past six months), the ratio by level of gratitude, and the trend in the amount of gratitude.

According to this embodiment, for example, the type of gratitude or the degree of gratitude can be easily conveyed to the other person. Specifically, for example, even when it is embarrassing to convey gratitude directly, when it is difficult to convey gratitude in front of a large group, when the other person is far away, or when the timing to convey the gratitude has been missed, the device and method of this embodiment can be used to easily convey gratitude. For this reason, when used in an organization in a company, for example, the device and method of this embodiment can increase mutual trust, and as a result, can be useful in improving the performance of individuals and the organization. Therefore, the gratitude data and statistical information in this embodiment are useful as gratitude data transmission history information in the device and method described in the first and second embodiments.

[Embodiment 4]
This embodiment is an example of a recommended activity information proposal support device of the present invention.

It is known that organizations undertake activities to improve the well-being (physical, mental, and social well-being) of their members. However, in order to propose appropriate activities to members of an organization, it is necessary to analyze the state of the organization and its members. However, in organizations such as workplaces, for example, the environment is subject to rapid changes due to frequent reassignments of members, making these analyses difficult.

The recommended activity information proposal support device of the present invention includes a state analysis unit, a recommended activity information extraction unit, and a recommended activity information output unit, the state analysis unit being the state analysis device of the present invention, the recommended activity information extraction unit extracts recommended activity information linked to a combination of the state of the organization and the state of its members, and the recommended activity information output unit outputs the extracted recommended activity information.

The recommended activity information proposal support device of this embodiment will be described with reference to FIG. 19. FIG. 19 is a block diagram showing an example of the configuration of the recommended activity information proposal support device 30 of this embodiment. As shown in FIG. 19, the recommended activity information proposal support device 30 includes a state analysis unit (state analysis device) 10, a recommended activity information extraction unit 31, and a recommended activity information output unit 32. Although not shown, the recommended activity information proposal support device 30 may include a storage unit. The recommended activity information proposal support device 30 of this embodiment may be incorporated into a server as a system. In this case, the server may be, for example, the state analysis device of the present invention. The recommended activity information proposal support device 30 of this embodiment may be a personal computer (PC) in which the program of the present invention is installed. Although not shown, the recommended activity information proposal support device 30 may be connectable to at least one of an external device and an external terminal of a device manager via a communication line network. When the recommended activity information proposal support device 30 is connectable to the external terminal of the device manager, the device manager may manage the recommended activity information proposal support device 30 from the external terminal.

The communication network is not particularly limited and may be a known network, for example, wired or wireless. The communication network is, for example, as described above.

The external device may be, for example, a PC; a mobile device such as a mobile phone, a smartphone, or a tablet; a smart watch, smart glasses, or a wearable device. The external device may be equipped with, for example, an imaging means such as a camera or a scanner, an IC (integrated circuit) card reader, or a voice input means such as a microphone.

Figure 20 shows an example block diagram of the hardware configuration of the recommended activity information proposal support device 30. The recommended activity information proposal support device 30 includes, for example, a CPU (central processing unit) 301, a memory 302, a bus 303, a storage device 304, an input device 306, a display 307, and a communication device (communication unit) 308. Each part of the recommended activity information proposal support device 30 is connected via the bus 303 by its respective interface (I/F).

The CPU 301 cooperates with other components, for example, through a controller (system controller, I/O controller, etc.), and is responsible for overall control of the recommended activity information proposal support device 30. In the recommended activity information proposal support device 30, the CPU 301 executes, for example, the program 305 of the present invention and other programs, and also reads and writes various information. Specifically, for example, the CPU 301 functions as a state analysis unit 10, a recommended activity information extraction unit 31, and a recommended activity information output unit 32. The recommended activity information proposal support device 30 includes a CPU as a computing device, but may also include other computing devices such as a GPU (Graphics Processing Unit) or an APU (Accelerated Processing Unit), or may include a combination of the CPU and these.

The memory 302 includes, for example, a main memory. The main memory is also called a primary storage device. When the CPU 301 performs processing, the memory 302 reads various operation programs, such as the program 305 of the present invention, stored in, for example, a storage device 304 (auxiliary storage device) described below. The CPU 301 then reads data from the memory 302, decodes it, and executes the program. The main memory is, for example, a RAM (random access memory). The memory 302 further includes, for example, a ROM (read only memory).

The bus 303 can also be connected to, for example, external devices. Examples of the external devices include an imaging device such as a camera, the external device, an external storage device, a printer, and an audio output device such as a speaker. The recommended activity information proposal support device 30 can be connected to the communication line network by, for example, a communication device 308 connected to the bus 303, and can also be connected to the external devices via the communication line network.

The storage device 304 is also called an auxiliary storage device, as opposed to the main memory. As described above, the storage device 304 stores an operating program including the program 305 of the present invention. The storage device 304 includes, for example, a storage medium and a drive for reading and writing data from and to the storage medium. The storage medium is not particularly limited, and may be, for example, an internal or external type, and may be, for example, a hard disk drive (HDD), a floppy disk (FD), a CD-ROM, a CD-R, a CD-RW, an MO, a DVD, a flash memory, a memory card, or the like, and the drive is not particularly limited. The storage device 304 may be, for example, a hard disk drive (HDD) in which the storage medium and the drive are integrated, and a solid state drive (SSD). When the recommended activity information proposal support device 30 includes the storage unit, the storage device 304 may function as, for example, the storage unit, and may store recommended activity information linked to a combination of the state of the organization and the state of the members. The recommended activity information will be described later.

The recommended activity information proposal support device 30 further includes, for example, an input device 306 and a display 307. Examples of the input device 306 include pointing devices such as a touch panel, track pad, and mouse; a keyboard; imaging means such as a camera and scanner; card readers such as an IC card reader and a magnetic card reader; and audio input means such as a microphone. Examples of the display 307 include display devices such as an LED display and a liquid crystal display. In this embodiment, the input device 306 and the display 307 are configured separately, but the input device 306 and the display 307 may be configured as one unit, such as a touch panel display.

In the recommended activity information proposal support device 30, the memory 302 and storage device 304 can store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the device 30, and information used by the device 30 when executing processing. Note that at least a portion of the information may be stored, for example, in an external server other than the memory 302 and storage device 304, or may be stored in a distributed manner on multiple terminals using blockchain technology or the like.

Next, the recommended activity information proposal support method of this embodiment will be described with reference to the flowchart of FIG. 21. The recommended activity information proposal support method of this embodiment can be implemented, for example, by using the recommended activity information proposal support device 30 of this embodiment shown in FIG. 19 and FIG. 20. Note that the recommended activity information proposal support method of the present invention is not limited to the use of the recommended activity information proposal support device 30.

First, the state of the organization and the state of the members are analyzed by the state analysis unit 10 (S31, state analysis step). As described above, since the state analysis unit 10 is the state analysis device 10 of the present invention, S31 can be performed in the same manner as S1 to S6 in the first embodiment, and the explanations of the first and second embodiments can be used.

Next, the recommended activity information extraction unit 31 extracts recommended activity information linked to a combination of the state of the organization and the state of the members (S32, recommended activity information extraction step). The recommended activity information may be linked to, for example, a combination of the state of the organization and the state of the members, and may further be linked to a recommendation score indicating the degree of recommendation of the recommended activity information for the combination. Specific examples of the recommended activity information will be described later. The recommended activity information may be stored, for example, in the storage device 304 of the recommended activity information proposal support device 30, or may be stored in a database outside the device. In the latter case, the recommended activity information extraction unit 31 extracts the recommended activity information from the database outside the device via the communication line network. The recommended activity information extraction unit 31 may extract, for example, one type of recommended activity information for the combination, or may extract two or more types of recommended activity information. In the latter case, for example, the recommended activity information may be extracted in descending order of the recommendation score in a ranking format, for example, the recommended activity information with the highest recommendation score to the recommended activity information with the fifth highest recommendation score may be extracted.

The recommended activity information is, for example, information on activities that are considered to be useful for improving the well-being (physical, mental, and social well-being) of members in an organization, and is not particularly limited, and any information can be used. Specific examples of the recommended activity information include information on activities such as playing, taking a walk, talking with others, meditating, positive imagination, singing, dancing, reading, writing a diary, and listening to others. The recommended activity information is not limited to the above examples, and may be, for example, information on activities introduced in the following references.
References: the University of California, Berkeley, “Find Your Pathway to Happiness! Discover simple steps to boost your well-being.”, [online], [searched on September 5, 2021], Internet <URL: https://ggia.berkeley.edu/>

Figure 22 shows a specific example of recommended activity information and recommendation scores linked to a combination of organizational state and member state. Figure 22 (A) is an example of recommended activity information and recommendation scores when the organizational state is in a chaotic period and the member state is in the first quadrant, Figure 22 (B) is an example of recommended activity information and recommendation scores when the organizational state is in a chaotic period and the member state is in the second quadrant, and Figure 22 (C) is an example of recommended activity information and recommendation scores when the organizational state is in a chaotic period and the member state is in the third quadrant. Note that the present invention is in no way limited to these examples.

Then, the recommended activity information output unit 32 outputs the extracted recommended activity information (S33, recommended activity information output step). The output by the recommended activity information output unit 32 may be, for example, output (display) on the display 307 of the device 30, or may be output to an external device via the communication line network. An example of the external device is a terminal of the member. Furthermore, the recommended activity information output unit 32 may output, for example, the organizational state and the member state in addition to the recommended activity information.

The recommended activity information proposal support device of this embodiment can extract and output activities that can improve the well-being of members based on the organizational state and individual state analyzed by the state analysis device of the present invention. Therefore, the recommended activity information proposal support device of this embodiment can be used to propose methods for improving the well-being of members in an organization.

[Embodiment 5]
This embodiment is another example of a recommended activity information proposal support device.

The recommended activity information proposal support device of this embodiment is similar to the recommended activity information proposal support device 30 of the above-mentioned embodiment 4, except that in addition to the configuration of the recommended activity information proposal support device 30 of embodiment 4, it includes an activity information acquisition unit, a score calculation unit, and a score update unit, and the description thereof can be used. The recommended activity information proposal support device 30A of this embodiment includes, for example, an activity information acquisition unit 33, a score calculation unit 34, and a score update unit 35, and the recommended activity information is linked to a recommendation score for each combination of the state of the organization and the state of the member, the activity information acquisition unit 33 acquires the activity information of the member, the score calculation unit 34 calculates the score of the recommended activity information based on the activity information, and the score update unit 35 updates the recommendation score of the recommended activity information based on the calculated score.

Fig. 23 is a block diagram showing an example of the configuration of a recommended activity information proposal support device 30A of this embodiment. As shown in Fig. 23, the recommended activity information proposal support device 30A includes an activity information acquisition unit 33, a score calculation unit 34, and a score update unit 35 in addition to the configuration of the recommended activity information proposal support device 30 of embodiment 4. The hardware configuration of the recommended activity information proposal support device 30A is the same as that of the recommended activity information proposal support device 30 of Fig. 20, except that the CPU 301 includes the configuration of the recommended activity information proposal support device 30A of Fig. 23 instead of the configuration of the recommended activity information proposal support device 30 of Fig. 19.

Next, the recommended activity information proposal support method of this embodiment will be described with reference to the flowchart of FIG. 24. The recommended activity information proposal support method of this embodiment can be implemented, for example, by using the recommended activity information proposal support device 30A of this embodiment shown in FIG. 23. Note that the recommended activity information proposal support method of the present invention is not limited to the use of the recommended activity information proposal support device 30A.

First, steps S31 to S33 are carried out in the same manner as steps S31 to S33 in the method for supporting the proposal of recommended activity information in embodiment 4.

Next, the activity information acquisition unit 33 acquires the member's activity information (S34, activity information acquisition step). The activity information is information in which the organizational state and the member's state are linked to information on the activities carried out by the member. The activity information may be, for example, information on activities during a predetermined period. The predetermined period is not particularly limited, and may be, for example, one day, three days, one week, one month, three months, six months, etc. The acquisition format may be, for example, acquisition from a database or server that stores the activity information via the communication line network, or acquisition from the member's terminal (also called a member terminal). Figure 25 shows an example of one week's activity information for a member whose organizational state is in a turbulent period and whose member state is in the first quadrant. In the activity names shown in Figure 25, the days marked with a circle are the days on which the member performed the activity, and blank spaces indicate the days on which the member did not perform the activity.

Next, the score calculation unit 34 calculates the score of the recommended activity information based on the activity information (S35, score calculation step). The score calculation unit 34 can calculate the score by, for example, dividing the number of days during the specified period during which the activity was performed by the number of days during the specified period. Specifically, based on the activity information shown in FIG. 25, since "playing pretend with children" was performed six days out of the seven days of the specified period, the score can be calculated as "0.85". Similarly, since "enjoying walks" was performed four days out of the seven days of the specified period, the score can be calculated as "0.57", since "making time with children" was performed two days out of the seven days of the specified period, the score can be calculated as "0.28", since "having conversations with others" was performed three days out of the seven days of the specified period, the score can be calculated as "0.42", and since "regulating a compassionate mind through meditation" was performed one day out of the seven days of the specified period, the score can be calculated as "0.14".

The score update unit 35 updates the recommendation score of the recommended activity information based on the calculated score (S36, score update step). Specifically, the score update unit 35 updates the recommendation score by adding the score calculated in S34 to the recommendation score linked to each combination of the organization's status and the member's status in the recommended activity information, for example. FIG. 26 shows an example of the recommendation score linked to the recommended activity information and the updated score updated by the score update unit 35.

The recommended activity information proposal support device 30A of this embodiment includes an activity information acquisition unit 33, a score calculation unit 34, and a score update unit 35, and therefore can update the recommendation score of the recommended activity information, for example, with a score calculated based on the actual activity of the member. Therefore, according to the recommended activity information proposal support device of this embodiment, it is possible to improve the accuracy of the recommended activity information proposal from the next time onwards, for example.

[Embodiment 6]
The first program of the present embodiment is a program for causing a computer to execute each step of the above-mentioned state analysis method. Specifically, the program of the present embodiment is a program for causing a computer to execute a gratitude data acquisition procedure, a network generation procedure, a network feature analysis procedure, an organization state identification procedure, a member state analysis procedure, and an output procedure.

The thank you data acquisition step acquires thank you data transmission history information indicating that thank you data has been transmitted from one member to another member;
The network generation step generates a member network within an organization to which the member belongs based on the gratitude data transmission history information;
The network feature analysis step includes analyzing a feature of the member network,
The organizational state identification step includes identifying an organizational state based on the feature amount of the analyzed member network;
The member status analysis step includes analyzing the status of the member based on a feature amount of the member network,
The output step outputs the organizational status and the member status.

The first program of this embodiment can also be said to be a program that causes a computer to function as a gratitude data acquisition procedure, a network generation procedure, a network feature analysis procedure, an organizational state identification procedure, a member state analysis procedure, and an output procedure.

The first program of this embodiment can use the description in the condition analysis device and condition analysis method of the present invention. For example, the "procedure" in each of the procedures can be read as "processing". The program of this embodiment can be recorded in a computer-readable recording medium. The recording medium is, for example, a non-transitory computer-readable storage medium. The recording medium is not particularly limited, and examples include random access memory (RAM), read-only memory (ROM), hard disk (HD), optical disk, and floppy (registered trademark) disk (FD).

[Embodiment 7]
The second program of the present embodiment is a program for causing a computer to execute each step of the above-mentioned method for supporting proposal of recommended activity information. Specifically, the program of the present embodiment is a program for causing a computer to execute a state analysis step, a recommended activity information extraction step, and a recommended activity information output step.

the condition analysis procedure is a condition analysis method executed by the first program of the present invention,
The recommended activity information extraction step includes extracting recommended activity information associated with a combination of a state of the organization and a state of each member;
The recommended activity information output step outputs the extracted recommended activity information.

The second program of this embodiment can also be said to be a program that causes a computer to function as a program for executing a status analysis procedure, a recommended activity information extraction procedure, and a recommended activity information output procedure.

The second program of this embodiment can use the description in the recommended activity information proposal support device and the recommended activity information proposal support method of the present invention. For example, the "procedure" in each of the steps can be read as "processing". The program of this embodiment may be recorded in a computer-readable recording medium. The recording medium is, for example, a non-transitory computer-readable storage medium. The recording medium is not particularly limited, and examples thereof include random access memory (RAM), read-only memory (ROM), hard disk (HD), optical disk, and floppy (registered trademark) disk (FD).

The present invention has been described above with reference to the embodiments, but the present invention is not limited to the above embodiments. Various modifications that can be understood by a person skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

<Additional Notes>
A part or all of the above-described embodiments can be described as follows, but is not limited to the following.
(Appendix 1)
The system includes a gratitude data acquisition unit, a network generation unit, a network feature analysis unit, an organization state identification unit, a member state analysis unit, and an output unit,
the thank you data acquisition unit acquires thank you data transmission history information indicating that thank you data has been transmitted from one member to another member;
The network generation unit generates a member network within an organization to which the member belongs based on the gratitude data transmission history information,
The network feature analysis unit analyzes features of the member network,
The organizational state identification unit identifies an organizational state based on the feature amount of the analyzed member network,
The member status analysis unit analyzes the status of the member based on the feature amount of the member network,
The output unit outputs the organizational state and the member states.
(Appendix 2)
The network feature analysis unit further determines a network type of the member network from the feature,
2. The state analysis device according to claim 1, wherein the organization state identification unit identifies the organization state based on the network type.
(Appendix 3)
The gratitude data transmission history information includes attribute information of the one member and attribute information of the other member,
The network generation unit generates the member network in which attribute information of each member is linked,
3. The status analysis device according to claim 1, wherein the member status analysis unit calculates an approval level and interpersonal satisfaction level of each member from the feature amount, and analyzes the status of the member based on the approval level and interpersonal satisfaction level of each member.
(Appendix 4)
The system includes a state analysis unit, a recommended activity information extraction unit, and a recommended activity information output unit,
The state analysis unit is a state analysis device according to any one of Supplementary Note 1 to 3,
The recommended activity information extraction unit extracts recommended activity information associated with a combination of the state of the organization and the state of the members,
The recommended activity information output unit outputs the extracted recommended activity information.
(Appendix 5)
The present invention includes an activity information acquisition unit, a score calculation unit, and a score update unit,
The recommended activity information is associated with a recommendation score for each combination of the state of the organization and the state of the member,
The activity information acquisition unit acquires activity information of members,
The activity information is information in which the organizational status and the status of the members are linked to information on activities carried out by the members,
The score calculation unit calculates a score of the recommended activity information based on the activity information,
The recommended activity information proposal support device according to claim 4, wherein the score update unit updates the recommendation score of the recommended activity information based on the calculated score.
(Appendix 6)
The method includes a gratitude data acquisition step, a network generation step, a network feature analysis step, an organization status identification step, a member status analysis step, and an output step,
The thank you data acquisition step acquires thank you data transmission history information indicating that thank you data has been transmitted from one member to another member,
The network generating step generates a member network within an organization to which the member belongs based on the gratitude data transmission history information,
The network feature analysis step includes analyzing a feature of the member network,
The organizational state identification step includes identifying an organizational state based on the feature amount of the analyzed member network,
The member status analysis step includes analyzing the status of the member based on a feature amount of the member network,
The output step outputs the organizational status and the member status.
(Appendix 7)
The network feature analysis step further includes determining a network type of the member network from the feature,
The condition analysis method according to claim 6, wherein the tissue condition identifying step identifies the tissue condition based on the network type.
(Appendix 8)
The gratitude data transmission history information includes attribute information of the one member and attribute information of the other member,
The network generating step generates the member network in which attribute information of each member is linked,
8. The status analysis method according to claim 6, wherein the member status analysis step calculates an approval level and an interpersonal satisfaction level of each member from the feature amount, and analyzes the status of the member based on the approval level and the interpersonal satisfaction level of each member.
(Appendix 9)
The method includes a state analysis step, a recommended activity information extraction step, and a recommended activity information output step,
The state analysis step is a state analysis method according to any one of Supplementary Notes 6 to 8,
The recommended activity information extraction step extracts recommended activity information associated with a combination of the state of the organization and the state of the members,
The recommended activity information suggestion support method includes outputting the extracted recommended activity information in the recommended activity information output step.
(Appendix 10)
The method includes an activity information acquisition step, a score calculation step, and a score update step,
The recommended activity information is associated with a recommendation score for each combination of the state of the organization and the state of the member,
The activity information acquisition step acquires activity information of members,
The activity information is information in which the organizational status and the status of the members are linked to information on activities carried out by the members,
The score calculation step calculates a score of the recommended activity information based on the activity information,
The recommended activity information suggestion support method according to claim 9, wherein the score update step updates the recommendation score of the recommended activity information based on the calculated score.
(Appendix 11)
A program for causing a computer to execute a procedure for acquiring gratitude data, a procedure for generating a network, a procedure for analyzing network features, a procedure for identifying an organization's state, a procedure for analyzing a member's state, and a procedure for outputting the data,
The thank you data acquisition step acquires thank you data transmission history information indicating that thank you data has been transmitted from one member to another member;
The network generation step generates a member network within an organization to which the member belongs based on the gratitude data transmission history information;
The network feature analysis step includes analyzing a feature of the member network,
The organizational state identification step includes identifying an organizational state based on the feature amount of the analyzed member network;
The member status analysis step includes analyzing the status of the member based on a feature amount of the member network,
The output step outputs the organization status and the member status.
(Appendix 12)
The network feature analysis step further includes determining a network type of the member network from the feature;
12. The program of claim 11, wherein the organizational state identification procedure identifies an organizational state based on the network type.
(Appendix 13)
The gratitude data transmission history information includes attribute information of the one member and attribute information of the other member,
The network generation step generates the member network to which attribute information of each member is linked,
13. The status analysis method according to claim 11, wherein the member status analysis step calculates an approval level and interpersonal satisfaction level of each member from the feature amount, and analyzes the status of the member based on the approval level and interpersonal satisfaction level of each member.
(Appendix 14)
A program for causing a computer to execute a status analysis procedure, a recommended activity information extraction procedure, and a recommended activity information output procedure,
The status analysis procedure is a status analysis method executed by a program according to any one of Supplementary Notes 11 to 13,
The recommended activity information extraction step includes extracting recommended activity information associated with a combination of a state of the organization and a state of each member;
The recommended activity information output step outputs the extracted recommended activity information.
(Appendix 15)
The method includes an activity information acquisition step, a score calculation step, and a score update step,
The recommended activity information is associated with a recommendation score for each combination of the state of the organization and the state of the member,
The activity information acquisition step acquires activity information of members,
The activity information is information in which the organizational status and the status of the members are linked to information on activities carried out by the members,
The score calculation step includes calculating a score of the recommended activity information based on the activity information;
The program described in Appendix 14, wherein the score update step updates the recommendation score of the recommended activity information based on the calculated score.
(Appendix 16)
A computer-readable recording medium having a program according to any one of appendices 12 to 15 recorded thereon.

The present invention makes it possible to grasp the status of an organization and the members belonging to the organization. Therefore, the present invention is useful, for example, in various fields that have organizations made up of multiple members.

10 State analysis device (state analysis unit)
11 gratitude data acquisition unit 12 network generation unit 13 network feature amount analysis unit 14 organization state identification unit 15 member state analysis unit 16 output unit 101 CPU
102 Memory 103 Bus 104 Storage device 105 Program 106 Input device 107 Display device 108 Communication device 20 Gratitude transmission device 21 Storage unit 22 Display unit 23 Selection unit 24 Transmitting/receiving unit 25 Statistics unit 30, 30A Recommended activity information proposal support device 31 Recommended activity information extraction unit 32 Recommended activity information output unit 33 Activity information acquisition unit 34 Score calculation unit 35 Score update unit 301 CPU
302 memory 303 bus 304 storage device 305 program 306 input device 307 display device 308 communication device

Claims (10)

The system includes a gratitude data acquisition unit, a network generation unit, a network feature analysis unit, an organization state identification unit, a member state analysis unit, and an output unit,
the thank you data acquisition unit acquires thank you data transmission history information indicating that thank you data has been transmitted from one member to another member;
The network generation unit generates a member network within an organization to which the member belongs based on the gratitude data transmission history information,
The network feature analysis unit analyzes features of the member network,
The organizational state identification unit identifies an organizational state based on the feature amount of the analyzed member network,
The member status analysis unit analyzes the status of the member based on the feature amount of the member network,
The output unit outputs the organizational state and the member states. The network feature analysis unit further determines a network type of the member network from the feature,
The state analysis device according to claim 1 , wherein the organization state identification unit identifies the organization state based on the network type. The gratitude data transmission history information includes attribute information of the one member and attribute information of the other member,
The network generation unit generates the member network in which attribute information of each member is linked,
3 . The status analysis device according to claim 1 , wherein the member status analysis unit calculates an approval level and interpersonal satisfaction level of each member from the feature amount, and analyzes the status of the member based on the approval level and interpersonal satisfaction level of each member. The system includes a state analysis unit, a recommended activity information extraction unit, and a recommended activity information output unit,
The state analysis unit is a state analysis device according to claim 1 ,
The recommended activity information extraction unit extracts recommended activity information associated with a combination of the state of the organization and the state of the members,
The recommended activity information output unit outputs the extracted recommended activity information. The present invention includes an activity information acquisition unit, a score calculation unit, and a score update unit,
The recommended activity information is associated with a recommendation score for each combination of the state of the organization and the state of the member,
The activity information acquisition unit acquires activity information of members,
The activity information is information in which the organizational status and the status of the members are linked to information on activities carried out by the members,
The score calculation unit calculates a score of the recommended activity information based on the activity information,
The recommended activity information proposal support device according to claim 4 , wherein the score update unit updates the recommendation score of the recommended activity information based on the calculated score. The method includes a gratitude data acquisition step, a network generation step, a network feature analysis step, an organization status identification step, a member status analysis step, and an output step,
The thank you data acquisition step acquires thank you data transmission history information indicating that thank you data has been transmitted from one member to another member,
The network generating step generates a member network within an organization to which the member belongs based on the gratitude data transmission history information,
The network feature analysis step includes analyzing a feature of the member network,
The organizational state identification step includes identifying an organizational state based on the feature amount of the analyzed member network,
The member status analysis step includes analyzing the status of the member based on a feature amount of the member network,
The output step outputs the organizational status and the member status.
A condition analysis method in which each step is executed by a computer . The method includes a state analysis step, a recommended activity information extraction step, and a recommended activity information output step,
The state analysis step is a state analysis method according to claim 6,
The recommended activity information extraction step extracts recommended activity information associated with a combination of the state of the organization and the state of the members,
The recommended activity information output step outputs the extracted recommended activity information.
A method for supporting the proposal of recommended activity information , in which each step is executed by a computer . A program for causing a computer to execute a procedure for acquiring gratitude data, a procedure for generating a network, a procedure for analyzing network features, a procedure for identifying an organization's state, a procedure for analyzing a member's state, and a procedure for outputting the data,
The thank you data acquisition step acquires thank you data transmission history information indicating that thank you data has been transmitted from one member to another member;
The network generation step generates a member network within an organization to which the member belongs based on the gratitude data transmission history information;
The network feature analysis step includes analyzing a feature of the member network,
The organizational state identification step includes identifying an organizational state based on the feature amount of the analyzed member network;
The member status analysis step includes analyzing the status of the member based on a feature amount of the member network,
The output step outputs the organization status and the member status. A program for causing a computer to execute a status analysis procedure, a recommended activity information extraction procedure, and a recommended activity information output procedure,
The status analysis step is a status analysis method executed by a program according to claim 8 ,
The recommended activity information extraction step includes extracting recommended activity information associated with a combination of a state of the organization and a state of each member;
The recommended activity information output step outputs the extracted recommended activity information. A computer-readable recording medium having the program according to claim 8 or 9 recorded thereon.

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