Measuring the controversy level of Arabic trending topics on Twitter

Abstract

Social micro-blogging systems like Twitter are used today as a platform that enables its users to write down about different topics. One important aspect of such human interactions is the existence of debate and disagreement. The most heated debates are found on controversial topics. Detecting such topics can be very beneficial in understanding the behavior of online social networks users and the dynamics of their interactions. Such an understanding leads to better ways of handling and predicting how the "online crowds" will act. Several approaches have been proposed for detecting controversy in online communication. Some of them represent the interactions in the form of graphs and study their properties in order to determine whether the topic of interaction is controversial or not. Other approaches rely on the content of the exchanged messages. In this study, we focus on the former approach in identifying the controversy level of the trending topics on Twitter. Unlike many previous works, we do not limit ourselves to a certain domain. Moreover, we focus on social content written in Arabic about hot events occurring in the Middle East. To the best of our knowledge, ours is the first work to undertake this approach in studying controversy in general topics written in Arabic. We collect a large dataset of tweets on different trending topics from different domains. We apply several approaches for controversy detection and compare their outcomes to determine which one is the most consistent measure.