Interactive Visual Analysis of Transcribed Multi-Party Discourse
Peer-Reviewed
Hautli-Janisz, Annette, Mennatallah El-Assady, Valentin Gold, Miriam Butt, Katharina Holzinger, and Daniel A. Keim. “Interactive Visual Analysis of Transcribed Multi-Party Discourse”. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL): Systems Demonstrations, pp. 49–54, Stroudsburg, PA. 2017.
We present the first web-based Visual Analytics framework for the analysis of multi-party discourse data using verbatim text transcripts. Our framework supports a broad range of server-based processing steps, ranging from data mining and statistical analysis to deep linguistic parsing of English and German. On the client-side, browser-based Visual Analytics components enable multiple perspectives on the analyzed data. These interactive visualizations allow exploratory content analysis, argumentation pattern review and speaker interaction modeling.