Identifying Opinion Subgroups in Arabic Online Discussions
Amjad Abu-Jbara, Ben King, Mona Diab and Dragomir Radev
The 51st Annual Meeting of the Association for Computational Linguistics - Short Papers (ACL Short Papers 2013)
Sofia, Bulgaria, August 4-9, 2013
In this paper, we study how Arabic natural language processing techniques can be used to analyze Arabic debates. The goal is to identify how the participants in a discussion split into subgroups with contrasting opinions. The members of a subgroup share the same opinion with respect to the discussion topic and an opposing opinion to the members of other subgroups. We use opinion mining techniques to identify opinionated text and the opinion targets. We represent the discussion in the form of opinion vector spaces, one vector per discussant. We identify opinion subgroups by clustering the vector space. We evaluate the system using a data set of labeled discussions and show that it achieves good results.
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