ChatMiner - Mining conversational content for topic modelling and author identification

In this project we will use the latest models of statistical content analysis that are proving successful in the areas of text mining and information retrieval for the mining of conversational content (e.g. Twetter, FaceBook, etc.) for topic identification (what is the conversation about?) and author identification (who are the people involved in the conversation?). Thus, the work proposed has four measurable objectives: (1) Develop a proper evaluation framework for mining conversational content; (2) Develop a number of models for topic modelling and authorship profiling for conversational content; (3) Develop an integrated model for topic and author identification/profiling of conversational content; (4) Implement and evaluate a demonstration system of the above integrated model in a realistic application scenario. These objectives will be achieved by applying to the mining of conversational content our past experience in text mining, language and topic modelling, and user/author profiling acquired in a number of past and current research projects. In addition, the project will take advantage and strengthen existing collaborations between the applicants and some very strong research groups in language and topic modelling and author identification.