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In this paper we perform an analytic comparison of a number of techniques used to detect fake and deceptive online reviews. We apply a number machine learning approaches found to be effective, and introduce our own approach by fine-tuning state of th
Externí odkaz:
http://arxiv.org/abs/2010.15296
Publikováno v:
ACL (2)
Kennedy, Steffan, Walsh, Niall, Sloka, Kirils, McCarren, Andrew ORCID: 0000-0002-7297-0984 and Foster, Jennifer ORCID: 0000-0002-7789-4853 (2019) Fact or factitious? Contextualized opinion spam detection. In: 57th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, 28 Jul-2 Aug 2019, Florence, Italy.
Kennedy, Steffan, Walsh, Niall, Sloka, Kirils, McCarren, Andrew ORCID: 0000-0002-7297-0984
In this paper we perform an analytic comparison of a number of techniques used to detect fake and deceptive online reviews. We apply a number machine learning approaches found to be effective, and introduce our own approach by fine-tuning state of th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9f8c962013cf51aaaf1d96f1478be64
http://arxiv.org/abs/2010.15296
http://arxiv.org/abs/2010.15296