Biblio

Analyzing and gaining insights from a large amount of textual conversations can be quite challenging for a user, especially when the discussions become very long. During my doctoral research, I have focused on integrating Information Visualization (InfoVis) with Natural Language Processing (NLP) techniques to better support the user's task of exploring and analyzing conversations. For this purpose, I have designed a visual text analytics system that supports the user exploration, starting from a possibly large set of conversations, then narrowing down to a subset of conversations, and eventually drilling-down to a set of comments of one conversation. While so far our approach is evaluated mainly based on lab studies, in my on-going and future work I plan to evaluate our approach via online longitudinal studies.