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arXiv · 1507.05224

Quantifying Controversy in Social Media

Kiran Garimella·Gianmarco De Francisci Morales·Aristides Gionis·Michael Mathioudakis
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Abstract

Which topics spark the most heated debates on social media? Identifying those topics is not only interesting from a societal point of view, but also allows the filtering and aggregation of social media content for disseminating news stories. In this paper, we perform a systematic methodological study of controversy detection by using the content and the network structure of social media. Unlike previous work, rather than study controversy in a single hand-picked topic and use domain specific knowledge, we take a general approach to study topics in any domain. Our approach to quantifying controversy is based on a graph-based three-stage pipeline, which involves (i) building a conversation graph about a topic; (ii) partitioning the conversation graph to identify potential sides of the controversy; and (iii) measuring the amount of controversy from characteristics of the graph. We perform an extensive comparison of controversy measures, different graph-building approaches, and data sources. We use both controversial and non-controversial topics on Twitter, as well as other external datasets. We find that our new random-walk-based measure outperforms existing ones in capturing the intuitive notion of controversy, and show that content features are vastly less helpful in this task.

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Kiran Garimella, Gianmarco De Francisci Morales, Aristides Gionis, Michael Mathioudakis. 2015-07-18. Quantifying Controversy in Social Media. https://arxiv.org/abs/1507.05224

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