Angry but Accurate: Detecting and Profiling the Counter-Misinformation Ecosystem on TwitterOn social media, many users actively push back against false claims.
- doi
- 10.1145/3800935.3830879
- isbn
- 979-8-4007-2564-7
- name
- Angry but Accurate: Detecting and Profiling the Counter-Misinformation Ecosystem on Twitter
- source
- html
- acm_url
- https://dl.acm.org/doi/10.1145/3800935.3830879
- authors
- Eun Cheol Choi, Emilio Ferrara
- doi_url
- https://doi.org/10.1145/3800935.3830879
- license
- CC BY 4.0
- summary
- On social media, many users actively push back against false claims.
- keywords
- counter-misinformation; social correction; misinformation; natural language inference; emotion detection; social media
- published
- 2026-09-14
- conference
- HT '26: 37th ACM Conference on Hypertext, London, United Kingdom, September 14–18, 2026
- acm_html_url
- https://dl.acm.org/doi/fullHtml/10.1145/3800935.3830879
- ccs_concepts
- CCS Concepts: • Human-centered computing → Social media ; Empirical studies in collaborative and social computing; • Computing methodologies → Natural language processing ; Machine learning;
- displayAuthor
- Eun Cheol Choi, Emilio Ferrara
- proceedings_url
- https://dl.acm.org/doi/proceedings/10.1145/3800935
- displayPublishTime
- 2026-09-14
- acm_reference_format
- ACM Reference Format: Eun Cheol Choi and Emilio Ferrara. 2026. Angry but Accurate: Detecting and Profiling the Counter-Misinformation Ecosystem on Twitter. In 37th ACM Conference on Hypertext (HT '26), September 14--18, 2026, London, United Kingdom. ACM, New York, NY, USA 7 Pages. https://doi.org/10.1145/3800935.3830879
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