Abstract
Studies on detecting and understanding the spread of unreliable news on social media have identified key characteristic differences between reliable and unreliable posts. These differences in language use also vary in expression across individuals, making it important to consider personal factors in unreliable news detection. The application of personalization methods for this has been made possible by recent publication of datasets with user histories, though this area is still largely unexplored. In this paper we present approaches to represent social media users in order to improve performance on three tasks: (1) classification of unreliable news posts, (2) classification of unreliable news spreaders, and, (3) prediction of the spread of unreliable news. We compare the User2Vec method from previous work to two other approaches; a learnable user embedding layer trained with the downstream task, and a representation derived from an authorship attribution classifier. We demonstrate that the implemented strategies substantially improve classification performance over state-of-the-art and provide initial results on the task of unreliable news prediction.- Anthology ID:
- 2024.woah-1.11
- Volume:
- Proceedings of the 8th Workshop on Online Abuse and Harms (WOAH 2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Yi-Ling Chung, Zeerak Talat, Debora Nozza, Flor Miriam Plaza-del-Arco, Paul Röttger, Aida Mostafazadeh Davani, Agostina Calabrese
- Venues:
- WOAH | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 146–158
- Language:
- URL:
- https://aclanthology.org/2024.woah-1.11
- DOI:
- Cite (ACL):
- Shaina Ashraf, Fabio Gruschka, Lucie Flek, and Charles Welch. 2024. Harnessing Personalization Methods to Identify and Predict Unreliable Information Spreader Behavior. In Proceedings of the 8th Workshop on Online Abuse and Harms (WOAH 2024), pages 146–158, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Harnessing Personalization Methods to Identify and Predict Unreliable Information Spreader Behavior (Ashraf et al., WOAH-WS 2024)
- PDF:
- https://preview.aclanthology.org/jeptaln-2024-ingestion/2024.woah-1.11.pdf