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
Venues:
ArgMining | EMNLP
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
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/2021.argmining-1.1.pdf