Support or Refute: Analyzing the Stance of Evidence to Detect Out-of-Context Mis- and Disinformation
Abstract
Mis- and disinformation online have become a major societal problem as major sources of online harms of different kinds. One common form of mis- and disinformation is out-of-context (OOC) information, where different pieces of information are falsely associated, e.g., a real image combined with a false textual caption or a misleading textual description. Although some past studies have attempted to defend against OOC mis- and disinformation through external evidence, they tend to disregard the role of different pieces of evidence with different stances. Motivated by the intuition that the stance of evidence represents a bias towards different detection results, we propose a stance extraction network (SEN) that can extract the stances of different pieces of multi-modal evidence in a unified framework. Moreover, we introduce a support-refutation score calculated based on the co-occurrence relations of named entities into the textual SEN. Extensive experiments on a public large-scale dataset demonstrated that our proposed method outperformed the state-of-the-art baselines, with the best model achieving a performance gain of 3.2% in accuracy.- Anthology ID:
- 2023.emnlp-main.259
- Volume:
- Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4268–4280
- Language:
- URL:
- https://aclanthology.org/2023.emnlp-main.259
- DOI:
- 10.18653/v1/2023.emnlp-main.259
- Cite (ACL):
- Xin Yuan, Jie Guo, Weidong Qiu, Zheng Huang, and Shujun Li. 2023. Support or Refute: Analyzing the Stance of Evidence to Detect Out-of-Context Mis- and Disinformation. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 4268–4280, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Support or Refute: Analyzing the Stance of Evidence to Detect Out-of-Context Mis- and Disinformation (Yuan et al., EMNLP 2023)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2023.emnlp-main.259.pdf