Chatbot-assisted Community Analysis

Community Information Systems support professional communities of practice in organizing their work and learning processes on the Web. We have developed and extended the MobSOS (Mobile Community Information System 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). On the other hand, we have developed a Social Bot Framework which allows for a model-driven construction and utilization of social bots. With the latest enhancements, the bot is able to react on messages within a conversational channel. 

In this thesis, we want combine the MobSOS framework with the Social Bot Framework to query aggregated usage data and visualizations via chat. The goal of this thesis is a chatbot that is able to use the integration of post-mortem dumps (Mediabases) in MobSOS and allows communities an easy access to continuous community analytics.