#Brexit: Leave or Remain? The Role of User's Community and Diachronic Evolution on Stance Detection
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Abstract (arXiv)
Interest has grown around the classification of stance that users assume within online debates in recent years. Stance has been usually addressed by considering users posts in isolation, while social studies highlight that social communities may contribute to influence users' opinion. Furthermore, stance should be studied in a diachronic perspective, since it could help to shed light on users' opinion shift dynamics that can be recorded during the debate. We analyzed the political discussion in UK about the BREXIT referendum on Twitter, proposing a novel approach and annotation schema for stance detection, with the main aim of investigating the role of features related to social network community and diachronic stance evolution. Classification experiments show that such features provide very useful clues for detecting stance.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Jul 2020.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2.
5 papers.
- 2021Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Languagecited by 6
- 2022Writing about COVID-19 vaccines: Emotional profiling unravels how mainstream and alternative press framed AstraZeneca, Pfizer and vaccination campaignscited by 3
- 2022Language Independent Stance Detection: Social Interaction-based Embeddings and Large Language Modelscited by 2
- 2023Robust Stance Detection: Understanding Public Perceptions in Social Mediacited by 2
- 2023UstanceBR: a social media language resource for stance predictioncited by 0
- 2023UstanceBR: a social media language resource for stance prediction11 Dec 2023
- 2023Robust Stance Detection: Understanding Public Perceptions in Social Media26 Sep 2023
- 2022Language Independent Stance Detection: Social Interaction-based Embeddings and Large Language Models11 Oct 2022
- 2022Writing about COVID-19 vaccines: Emotional profiling unravels how mainstream and alternative press framed AstraZeneca, Pfizer and vaccination campaigns19 Jan 2022
- 2021Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Language13 Sep 2021