Post-Mortem Community Information Systems Success Analytics
Goal of this thesis is an integration of post-mortem community data dumps with the MobSOS real-time community information systems success awareness framework.
Community Information Systems support professional communities of practice in organizing their work and learning processes on the Web. We have developed the MobSOS (Mobile Oracle for Success) as comprehensive framework for community information systems success awareness. Communities thereby extract, collect, measure, visualize, and negotiate visualize relevant success factors from real-time and historical community log and survey response data in community information systems success models. Overall success thereby relates to technical system quality (e.g. reliability, user experience) and the system's impact on community practice (e.g. attraction of new members, outcome improvements). In this thesis, we want to apply the MobSOS framework on post-mortem community data collected across different media technologies (mailing lists, blogs, forums, etc.). Goal of this thesis is an integration of post-mortem dumps (Mediabases) in MobSOS to allow for a coherent community information systems success awareness within and beyond the lifetime of communities.
The master student should bring good skills in programming and an interest in data mining and statistics.