Which side are you on? Insider-Outsider classification in conspiracy-theoretic social media

Pavan Holur, Tianyi Wang, Shadi Shahsavari, Timothy Tangherlini, Vwani Roychowdhury


Abstract
Social media is a breeding ground for threat narratives and related conspiracy theories. In these, an outside group threatens the integrity of an inside group, leading to the emergence of sharply defined group identities: Insiders – agents with whom the authors identify and Outsiders – agents who threaten the insiders. Inferring the members of these groups constitutes a challenging new NLP task: (i) Information is distributed over many poorly-constructed posts; (ii) Threats and threat agents are highly contextual, with the same post potentially having multiple agents assigned to membership in either group; (iii) An agent’s identity is often implicit and transitive; and (iv) Phrases used to imply Outsider status often do not follow common negative sentiment patterns. To address these challenges, we define a novel Insider-Outsider classification task. Because we are not aware of any appropriate existing datasets or attendant models, we introduce a labeled dataset (CT5K) and design a model (NP2IO) to address this task. NP2IO leverages pretrained language modeling to classify Insiders and Outsiders. NP2IO is shown to be robust, generalizing to noun phrases not seen during training, and exceeding the performance of non-trivial baseline models by 20%.
Anthology ID:
2022.acl-long.341
Volume:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
May
Year:
2022
Address:
Dublin, Ireland
Editors:
Smaranda Muresan, Preslav Nakov, Aline Villavicencio
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4975–4987
Language:
URL:
https://aclanthology.org/2022.acl-long.341
DOI:
10.18653/v1/2022.acl-long.341
Bibkey:
Cite (ACL):
Pavan Holur, Tianyi Wang, Shadi Shahsavari, Timothy Tangherlini, and Vwani Roychowdhury. 2022. Which side are you on? Insider-Outsider classification in conspiracy-theoretic social media. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 4975–4987, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Which side are you on? Insider-Outsider classification in conspiracy-theoretic social media (Holur et al., ACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.acl-long.341.pdf
Software:
 2022.acl-long.341.software.zip
Data
SemEval-2014 Task-4