Abstract
Some fake online reviews may have overlapping textual features with authentic reviews. This paper explores the nuanced differences between helpful and unhelpful reviews, as well as fake and authentic reviews. Four textual features—polarity, subjectivity, readability, and depth—are used for the investigation. Results suggest that subjectivity, readability and depth help to distinguish between helpful and unhelpful reviews but not between fake and authentic ones. However, polarity offers a clue to differentiate between helpful fake and helpful authentic reviews. Specifically, for positive entries, helpful fake reviews contain more contents indicative of surprise while helpful authentic had more expectation-confirmed words like satisfaction. For negative entries, helpful fake reviews contained more contents indicative of anger while authentic helpful ones carried more anxiety.
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Acknowledgments
The authors would like to thank Tengtao Lin, Sung Yang Ho, and Fangyi Shen for their help in data collection and analysis.
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Chua, A.Y.K., Chen, X. (2022). Online “helpful” Lies: An Empirical Study of Helpfulness in Fake and Authentic Online Reviews. In: Smits, M. (eds) Information for a Better World: Shaping the Global Future. iConference 2022. Lecture Notes in Computer Science(), vol 13192. Springer, Cham. https://doi.org/10.1007/978-3-030-96957-8_10
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DOI: https://doi.org/10.1007/978-3-030-96957-8_10
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