Presented By: Parinaz Sobhani
Location: DL Pratt Building, 6 King's College Circle, Room 266
Abstract: Computational approaches to opinion mining have mostly focused on polarity detection of product reviews by classifying the given text as positive, negative or neutral. While, there is less effort in the direction of socio-political opinion mining to determine favourability towards given targets of interest, particularly for social media data like news comments and tweets. In this talk, we explore the task of automatically determining from the text whether the author of the text is in favour of, against, or neutral towards a proposition or target. This talk is organized into three main parts: the first part on Twitter stance detection and interaction of stance and sentiment labels, the second part on detecting stance and the reasons behind it in online news comments, and the third part on multi-target stance classification.