Stance detection in online discussions
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Abstract (arXiv)
This paper describes our system created to detect stance in online discussions. The goal is to identify whether the author of a comment is in favor of the given target or against. Our approach is based on a maximum entropy classifier, which uses surface-level, sentiment and domain-specific features. The system was originally developed to detect stance in English tweets. We adapted it to process Czech news commentaries.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Jan 2017.
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Citing papers per year: 2022: 4.
4 papers.
- 2022OpenStance: Real-world Zero-shot Stance Detectioncited by 7
- 2022ExaASC: A General Target-Based Stance Detection Corpus in Arabic Languagecited by 5
- 2022Legal and Political Stance Detection of SCOTUS Languagecited by 5
- 2022From Stance to Concern: Adaptation of Propositional Analysis to New Tasks and Domainscited by 4
- 2022Legal and Political Stance Detection of SCOTUS Language21 Nov 2022
- 2022OpenStance: Real-world Zero-shot Stance Detection25 Oct 2022
- 2022ExaASC: A General Target-Based Stance Detection Corpus in Arabic Language29 Apr 2022
- 2022From Stance to Concern: Adaptation of Propositional Analysis to New Tasks and Domains20 Mar 2022