Quantifying Controversy on Social Media
Research output: Contribution to journal › Article › Scientific › peer-review
- Qatar Computing Research Institute
- CNRS LIRIS
- INSA DE LYON
Unlike previous work, rather than studying controversy in a single hand-picked topic and using 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.
|Journal||ACM Transactions on Social Computing|
|Publication status||Published - 1 Jan 2018|
|MoE publication type||A1 Journal article-refereed|
- Controversy, echo chambers, filter bubble, polarization, twitter