SIG ODIS - Artificial Intelligence and Semantic Technologies for Intelligent Systems

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Paper Type

ERF

Paper Number

1308

Description

With the availability of information technologies, the number of online reviews is increasing day by day. As consumers utilize online reviews in their purchasing decisions, they need to know the genuineness of the reviews as non-genuine, i.e. fake, reviews result in both monetary and time losses. Furthermore, businesses also suffer financial loss due to fake reviews and face challenges in retaining consumers' trust. Recent studies show that almost one-third of online reviews are fake, and the consumer spending due to fake online reviews is $152 billion. As a result of its huge impact, it is vital for organizations, especially online review platforms, to mitigate fake reviews. In this study, we concentrated on the review content, and by utilizing text analytics, we proposed utilizing the emotional content of online reviews in fake online review detection. We believe such utilization will enable organizations to increase the efficiency of fake review detection systems.

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Aug 10th, 12:00 AM

Use of Emotions in Fake Review Detection

With the availability of information technologies, the number of online reviews is increasing day by day. As consumers utilize online reviews in their purchasing decisions, they need to know the genuineness of the reviews as non-genuine, i.e. fake, reviews result in both monetary and time losses. Furthermore, businesses also suffer financial loss due to fake reviews and face challenges in retaining consumers' trust. Recent studies show that almost one-third of online reviews are fake, and the consumer spending due to fake online reviews is $152 billion. As a result of its huge impact, it is vital for organizations, especially online review platforms, to mitigate fake reviews. In this study, we concentrated on the review content, and by utilizing text analytics, we proposed utilizing the emotional content of online reviews in fake online review detection. We believe such utilization will enable organizations to increase the efficiency of fake review detection systems.

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