Veritas annotator: Discovering the origin of a rumour
Azevedo, Lucas Moustafa, Mohamed
Azevedo, Lucas
Moustafa, Mohamed
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Publication Date
2019-11-03
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Type
Workshop paper
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Citation
Azevedo, Lucas , & Moustafa, Mohamed (2019). Veritas annotator: Discovering the origin of a rumour. Paper presented at the Second Workshop on Fact Extraction and VERification (FEVER), Hong Kong, China, 3-7 November.
Abstract
Defined as the intentional or unintentional spread of false information (K et al., 2019) through context and/or content manipulation, fake news has become one of the most serious problems associated with online information (Waldrop, 2017). Consequently, it comes as no surprise that Fake News Detection has become one of the major foci of various fields of machine learning and while machine learning models have allowed individuals and companies to automate decision-based processes that were once thought to be only doable by humans, it is no secret that the real-life applications of such models are not viable without the existence of an adequate training dataset. In this paper we describe the Veritas Annotator, a web application for manually identifying the origin of a rumour. These rumours, often referred as claims, were previously checked for validity by Fact-Checking Agencies.
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Publisher
Association for Computational Linguistics (ACL)
Publisher DOI
10.18653/v1/D19-6614
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Attribution-NonCommercial-NoDerivs 3.0 Ireland