Identifying Opinion Subgroups in Arabic Online Discussions

In this paper, we use Arabic natural language processing techniques to analyze Arabic debates. The goal is to identify how the participants in a discussion split into subgroups with contrasting opinions. The members of each 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 opinion expressions and determine their polarities and their targets. We opinion predictions to represent the discussion in one of two formal representations: signed attitude network or a space of attitude vectors. We identify opinion subgroups by partitioning the signed network representation or by clustering the vector space representation. We evaluate the system using a data set of labeled discussions and show that it achieves good results.