Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate
Muhammad Mahad Afzal Bhatti, Ahsan Suheer Ahmad, Joonsuk Park
Abstract
Twitter is a popular platform to share opinions and claims, which may be accompanied by the underlying rationale. Such information can be invaluable to policy makers, marketers and social scientists, to name a few. However, the effort to mine arguments on Twitter has been limited, mainly because a tweet is typically too short to contain an argument — both a claim and a premise. In this paper, we propose a novel problem formulation to mine arguments from Twitter: We formulate argument mining on Twitter as a text classification task to identify tweets that serve as premises for a hashtag that represents a claim of interest. To demonstrate the efficacy of this formulation, we mine arguments for and against funding Planned Parenthood expressed in tweets. We first present a new dataset of 24,100 tweets containing hashtag #StandWithPP or #DefundPP, manually labeled as SUPPORT WITH REASON, SUPPORT WITHOUT REASON, and NO EXPLICIT SUPPORT. We then train classifiers to determine the types of tweets, achieving the best performance of 71% F1. Our results manifest claim-specific keywords as the most informative features, which in turn reveal prominent arguments for and against funding Planned Parenthood.- Anthology ID:
- 2021.argmining-1.1
- Volume:
- Proceedings of the 8th Workshop on Argument Mining
- Month:
- November
- Year:
- 2021
- Address:
- Punta Cana, Dominican Republic
- Editors:
- Khalid Al-Khatib, Yufang Hou, Manfred Stede
- Venue:
- ArgMining
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1–11
- Language:
- URL:
- https://aclanthology.org/2021.argmining-1.1
- DOI:
- 10.18653/v1/2021.argmining-1.1
- Cite (ACL):
- Muhammad Mahad Afzal Bhatti, Ahsan Suheer Ahmad, and Joonsuk Park. 2021. Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate. In Proceedings of the 8th Workshop on Argument Mining, pages 1–11, Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate (Bhatti et al., ArgMining 2021)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2021.argmining-1.1.pdf