Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 27-29 |
| Number of pages | 3 |
| Journal | CEUR Workshop Proceedings |
| Volume | 2411 |
| 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
- General Computer Science