Cohesive Team Selection Based on a Social Network Model

Abstract

A method is disclosed that enables the selection of a team of people in an organization, such as a business enterprise, to participate in a task that involves communicating with each other, in which the selection of the team seeks to maximize the team cohesiveness. The illustrative embodiment of the present invention incorporates the use of a social network model to describe the communication pattern in the organization. Based on the relationship between the organization's social network structure and the cohesiveness between the people in the organization, the technique of the illustrative embodiment estimates the dyadic cohesiveness of each pair of people, which is defined as the expected value of relationship strength between each evaluated pair of people. One component of the relationship strength is the number of interactions between the two people in the pair. The technique of the illustrative embodiment then uses the cohesiveness estimates to select teams.

What is claimed is: 
     
         1 . A method comprising:
 determining, via a processor, for a person in an organization, a class membership probability for a class, wherein the class membership probability is based on one of a magnitude of communications, a direction of the communications, and favorability of the communications, wherein the communications are associated with the person and other members of the organization;   determining a relationship strength value between each pair of people in the organization based on the class membership probability, wherein the each pair comprises the person and another member of the organization; and   based on the relationship strength value, assigning the person to a team of people from the organization.   
     
     
         2 . The method of  claim 1 , wherein the organization is represented as a social network. 
     
     
         3 . The method of  claim 1 , wherein the class membership probability is further based on a Bayesian model. 
     
     
         4 . The method of  claim 1 , wherein the class comprises members of the organization with one of similar incoming communications density and similar outgoing communications density. 
     
     
         5 . The method of  claim 1 , wherein the class comprises members of the organization with a similar distribution of one of incoming interactions and outgoing interactions. 
     
     
         6 . The method of  claim 1 , wherein the communications comprise one of voice, audio, video, text, data, instant messaging, email, web, and chat. 
     
     
         7 . The method of  claim 1 , further comprising:
 recording and storing communications history associated with the person and the other members of the organization; and   determining the class membership probability further based on the communications history.   
     
     
         8 . A system comprising:
 a processor; and   a computer-readable storage device storing instructions which, when executed by the processor, cause the processor to perform operations comprising:   determining for a person in an organization, a class membership probability for a class, wherein the class membership probability is based on one of a magnitude of communications, a direction of the communications, and favorability of the communications, wherein the communications are associated with the person and other members of the organization;   determining a relationship strength value between each pair of people in the organization based on the class membership probability, wherein the each pair comprises the person and another member of the organization; and   based on the relationship strength value, assigning the person to a team of people from the organization.   
     
     
         9 . The system of  claim 8 , wherein the organization is represented as a social network. 
     
     
         10 . The system of  claim 8 , wherein the class membership probability is further based on a Bayesian model. 
     
     
         11 . The system of  claim 8 , wherein the class comprises members of the organization with one of similar incoming communications density and similar outgoing communications density. 
     
     
         12 . The system of  claim 8 , wherein the class comprises members of the organization with a similar distribution of one of incoming interactions and outgoing interactions. 
     
     
         13 . The system of  claim 8 , wherein the communications comprise one of voice, audio, video, text, data, instant messaging, email, web, and chat. 
     
     
         14 . The system of  claim 8 , wherein the computer-readable storage device stores additional instructions which, when executed by the processor, cause the processor to perform further operations comprising:
 recording and storing communications history associated with the person and the other members of the organization; and   determining the class membership probability further based on the communications history.   
     
     
         15 . A computer-readable storage device storing instructions which, when executed by a processor, cause the processor to perform operations comprising:
 determining for a person in an organization, a class membership probability for a class, wherein the class membership probability is based on one of a magnitude of communications, a direction of the communications, and favorability of the communications, wherein the communications are associated with the person and other members of the organization;   determining a relationship strength value between each pair of people in the organization based on the class membership probability, wherein the each pair comprises the person and another member of the organization; and   based on the relationship strength value, assigning the person to a team of people from the organization.   
     
     
         16 . The computer-readable storage device of  claim 15 , wherein the organization is represented as a social network. 
     
     
         17 . The computer-readable storage device of  claim 15 , wherein the class comprises members of the organization with one of similar incoming communications density and similar outgoing communications density. 
     
     
         18 . The computer-readable storage device of  claim 15 , wherein the class comprises members of the organization with a similar distribution of one of incoming interactions and outgoing interactions. 
     
     
         19 . The computer-readable storage device of  claim 15 , wherein the communications comprise one of voice, audio, video, text, data, instant messaging, email, web, and chat. 
     
     
         20 . The computer-readable storage device of  claim 15 , storing additional instructions which, when executed by the processor, cause the processor to perform further operations comprising:
 recording and storing communications history associated with the person and the other members of the organization; and   determining the class membership probability further based on the communications history.