Abstract
Defined as the intentional or unintentionalspread of false information (K et al., 2019)through context and/or content manipulation,fake news has become one of the most seriousproblems associated with online information(Waldrop, 2017). Consequently, it comes asno surprise that Fake News Detection hasbecome one of the major foci of variousfields of machine learning and while machinelearning models have allowed individualsand companies to automate decision-basedprocesses that were once thought to be onlydoable by humans, it is no secret that thereal-life applications of such models are notviable without the existence of an adequatetraining dataset. In this paper we describethe Veritas Annotator, a web application formanually identifying the origin of a rumour. These rumours, often referred as claims,were previously checked for validity byFact-Checking Agencies.- Anthology ID:
- D19-6614
- Volume:
- Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER)
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong, China
- Editors:
- James Thorne, Andreas Vlachos, Oana Cocarascu, Christos Christodoulopoulos, Arpit Mittal
- Venue:
- WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 90–98
- Language:
- URL:
- https://aclanthology.org/D19-6614
- DOI:
- 10.18653/v1/D19-6614
- Cite (ACL):
- Lucas Azevedo and Mohamed Moustafa. 2019. Veritas Annotator: Discovering the Origin of a Rumour. In Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER), pages 90–98, Hong Kong, China. Association for Computational Linguistics.
- Cite (Informal):
- Veritas Annotator: Discovering the Origin of a Rumour (Azevedo & Moustafa, 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/D19-6614.pdf