Capturing word choice patterns with LDA for fake review detection in sentiment analysis

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The usefulness of user-generated online reviews is hampered by fake reviews, often produced by clandestinely sponsored reviewers. Detecting fake reviews is a difficult task even for laypeople, and this has also been the case for previous automatic detection ap-proaches, which have only had a limited success. Earlier studies showed that people who tell lies or write deceptive reviews tend to select words unnaturally. We propose a novel approach to detecting fake reviews by applying a topic modeling method based on Latent Dirichlet Allocation (LDA). A unique contribution of this paper is to explicate some latent aspects of fake and truthful reviews by means of
Publisher
Association for Computing Machinery
Issue Date
2016-06-15
Language
English
Citation

6th International Conference on Web Intelligence, Mining and Semantics, WIMS 2016

DOI
10.1145/2912845.2912868
URI
http://hdl.handle.net/10203/224447
Appears in Collection
CS-Conference Papers(학술회의논문)
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