Modeling Socio-Cultural Phenomena in Online Multi-Party Discourse

Strzalkowski, Tomek (State University of New York - Albany and Polish Academy of Sciences) | Broadwell, George Aaron (State University of New York - Albany) | Stromer-Galley, Jennifer ( State University of New York - Albany ) | Shaikh, Samira (State University of New York - Albany) | Liu, Ting (State University of New York - Albany) | Taylor, Sarah (Lockheed Martin)

AAAI Conferences 

We present in this paper, the application of a novel approach to computational modeling, understanding and detection of social phenomena in online multi-party discourse. A two-tiered approach was developed to detect a collection of social phenomena deployed by participants, such as topic control, task control, disagreement and involvement. We discuss how the mid-level social phenomena can be reliably detected in discourse and these measures can be used to differentiate participants of online discourse. Our approach works across different types of online chat and we show results on two specific data sets.

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