Xiaoai Ren

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In this article, we present a novel approach towards the detection and modeling of complex social phenomena in multi-party discourse, including leadership, influence, pursuit of power and group cohesion. We have developed a two-tier approach that relies on observable and computable linguistic features of conversational text to make predictions about(More)
Recent advances in automated analysis of on-line chat data allow us to draw conclusions about social behavior, such as leadership, in small groups previously possible only through manual methods of observation and analysis. We have applied such methods to comparable English and Chinese language data, defined a new language use called Tension Focus, and(More)
In this paper, we report our efforts in building a multi-lingual multi-party online chat corpus (MMPC) in order to develop a firm understanding in a set of social constructs such as agenda control, influence, and leadership as well as to computationally model such constructs in online interactions. These automated models will help capture the dialogue(More)
In this article, we present our novel approach towards the detection and modeling of complex social phenomena in multi-party discourse, including leadership, influence, pursuit of power and group cohesion. We have developed a two-tier approach that relies on observable and computable linguistic features of conversational text to make predictions about(More)
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