A Tagging Based Tool for Clustering of Large Idea Collections in Computer Supported Facilitation

Computer support for collaborative work (CSCW) in companies has produced extensive productivity gains in recent years. One form of CSCW is computer supported meeting facilitation, which tries to combine the advantages of computer supported systems with the methods of facilitated meetings. The Fraunhofer IGD in cooperation with industrial partners develops Digital Moderation, a software to run computer supported facilitated meetings of various group-sizes. A facilitated meeting uses four different information-processing activities: generation, organisation, evaluation and communication. Generation is usually done with brainstorming-techniques, which enable the participants to create ideas. Computer supported meeting systems are generally very effective during idea generation because they allow all participants to create ideas in parallel. This task is very motivating for the group, because every participant feels involved in the process of expressing thoughts. Especially in large groups this can lead to a huge amount of ideas in a relatively short period of time. All generated ideas, typically several hundred, must be organised to proceed with the meeting. Idea organisation lets the participants structure and consolidate ideas. However, traditional organisation of large ideas collections is a difficult and time-consuming task which might decrease the group's satisfaction. This thesis develops a tagging based tool for clustering of large idea collections, which uses the characteristics of computer based processing to overcome these challenges, thus creating an animating experience for the participants of the meeting. To support the course of a whole facilitated meeting, the tool will be integrated into the Digital Moderation Software. The tagging based clustering tool fulfils several key conditions which come from two basic problem domains: clustering of ideas in facilitated meetings and tagging based structuring of items