Abstract
Calls to action on social media are known to be effective means of mobilization in social movements, and a frequent target of censorship. We investigate the possibility of their automatic detection and their potential for predicting real-world protest events, on historical data of Bolotnaya protests in Russia (2011-2013). We find that political calls to action can be annotated and detected with relatively high accuracy, and that in our sample their volume has a moderate positive correlation with rally attendance.- Anthology ID:
- D19-5005
- Volume:
- Proceedings of the Second Workshop on Natural Language Processing for Internet Freedom: Censorship, Disinformation, and Propaganda
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Editors:
- Anna Feldman, Giovanni Da San Martino, Alberto Barrón-Cedeño, Chris Brew, Chris Leberknight, Preslav Nakov
- Venue:
- NLP4IF
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 36–44
- Language:
- URL:
- https://aclanthology.org/D19-5005
- DOI:
- 10.18653/v1/D19-5005
- Cite (ACL):
- Anna Rogers, Olga Kovaleva, and Anna Rumshisky. 2019. Calls to Action on Social Media: Detection, Social Impact, and Censorship Potential. In Proceedings of the Second Workshop on Natural Language Processing for Internet Freedom: Censorship, Disinformation, and Propaganda, pages 36–44, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- Calls to Action on Social Media: Detection, Social Impact, and Censorship Potential (Rogers et al., NLP4IF 2019)
- PDF:
- https://preview.aclanthology.org/corrections-2024-07/D19-5005.pdf