Topical Positioning: A New Method for Predicting Opinion Changes in Conversation
نویسندگان
چکیده
In this paper, we describe a novel approach to automatically detecting and tracking discussion dynamics in Internet social media by focusing on attitude modeling of topics. We characterize each participant’s attitude towards topics as Topical Positioning, employ Topical Positioning Map to represent the positions of participants with respect to each other and track attitude shifts over time. We also discuss how we used participants’ attitudes towards system-detected meso-topics to reflect their attitudes towards the overall topic of conversation. Our approach can work across different types of social media, such as Twitter discussion and online chat room. In this article, we show results on Twitter data.
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