Automatic Detection of Team Roles in Computer Supported Collaborative Work

Abstract

Computer systems designed to support teamwork are environments that enable and enhance collaboration among users. These systems, named groupware, incorporate techniques that facilitate communication and coordination among team members to improve group performance. However, as not all team members are identical, it is important to study users' characteristics to build more productive teams. Team Roles Theory allows obtaining the best possible performance taking into account individual skills, combining the weaknesses of each role with the strengths of other team members. Therefore, it is essential in group formation to consider mind the role each member is capable of playing. Currently, each team member has to complete lengthy questionnaires to determine his team role. We propose an approach for automatic detection of team roles from the observation of user interactions in CSCW systems. Particularly, we apply Artificial Intelligence to obtain the team role that best suits a user's characteristics and behaviours. To achieve this, the performance of various classification algorithms was analyzed. The results show that our approach can detect team roles with high degrees of precision.