This position paper details ongoing work ex-ploring political tribalism in online discussions about Brexit. We use computational methods to analyze a Twitter dataset of significant size (over 7 million tweets spanning 32 months of conversations), using group identity keywords (e.g. Brexiteer, Remainer) as a proxy for trib-alism. Initial results indicate that levels of tribalism increase over time for all keywords, in particular for pro-EU ones (Remainer, Re-moaner). We also find a number of anoma-lies in the volume of tribal keyword use over time, which may relate to real-life political events. Here we discuss initial findings and briey present ideas for further research.
|Number of pages||3|
|Journal||CEUR Workshop Proceedings|
|Publication status||Published - 25 Jul 2019|
|Event||3rd International Workshop on Recent Trends in News Information Retrieval, NewsIR 2019 - Paris, France|
Duration: 25 Jul 2019 → …
ASJC Scopus subject areas
- Computer Science(all)