Tackling Fake News Detection by Continually Improving Social Context Representations using Graph Neural Networks

Nikhil Mehta, Maria Leonor Pacheco, Dan Goldwasser


Abstract
Easy access, variety of content, and fast widespread interactions are some of the reasons making social media increasingly popular. However, this rise has also enabled the propagation of fake news, text published by news sources with an intent to spread misinformation and sway beliefs. Detecting it is an important and challenging problem to prevent large scale misinformation and maintain a healthy society. We view fake news detection as reasoning over the relations between sources, articles they publish, and engaging users on social media in a graph framework. After embedding this information, we formulate inference operators which augment the graph edges by revealing unobserved interactions between its elements, such as similarity between documents’ contents and users’ engagement patterns. Our experiments over two challenging fake news detection tasks show that using inference operators leads to a better understanding of the social media framework enabling fake news spread, resulting in improved performance.
Anthology ID:
2022.acl-long.97
Volume:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1363–1380
Language:
URL:
https://aclanthology.org/2022.acl-long.97
DOI:
10.18653/v1/2022.acl-long.97
Bibkey:
Cite (ACL):
Nikhil Mehta, Maria Leonor Pacheco, and Dan Goldwasser. 2022. Tackling Fake News Detection by Continually Improving Social Context Representations using Graph Neural Networks. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1363–1380, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Tackling Fake News Detection by Continually Improving Social Context Representations using Graph Neural Networks (Mehta et al., ACL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.acl-long.97.pdf
Code
 hockeybro12/fakenews_inference_operators