Rhetorical Structure Approach for Online Deception Detection: A Survey
Francielle Vargas, Jonas D‘Alessandro, Zohar Rabinovich, Fabrício Benevenuto, Thiago Pardo
Abstract
Most information is passed on in the form of language. Therefore, research on how people use language to inform and misinform, and how this knowledge may be automatically extracted from large amounts of text is surely relevant. This survey provides first-hand experiences and a comprehensive review of rhetorical-level structure analysis for online deception detection. We systematically analyze how discourse structure, aligned or not with other approaches, is applied to automatic fake news and fake reviews detection on the web and social media. Moreover, we categorize discourse-tagged corpora along with results, hence offering a summary and accessible introductions to new researchers.- Anthology ID:
- 2022.lrec-1.635
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 5906–5915
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.635
- DOI:
- Cite (ACL):
- Francielle Vargas, Jonas D‘Alessandro, Zohar Rabinovich, Fabrício Benevenuto, and Thiago Pardo. 2022. Rhetorical Structure Approach for Online Deception Detection: A Survey. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 5906–5915, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Rhetorical Structure Approach for Online Deception Detection: A Survey (Vargas et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.lrec-1.635.pdf