In recent years, a new phenomenon called ‘Review Bomb’ has affected online rating systems. It occurs when a massive amount of accounts reviews a single product, usually negatively to make its reputation slump. This study analyses the differences among legitimate users and ‘review bombers’, using common classifiers and techniques from spam detection to identify suspicious reviews, by looking at both content and user’s features.

The detection of spam behaviour in review bomb

TOMASELLI Venera
Primo
;
Cantone Giulio Giacomo
Secondo
;
Mazzeo Valeria
Ultimo
2021-01-01

Abstract

In recent years, a new phenomenon called ‘Review Bomb’ has affected online rating systems. It occurs when a massive amount of accounts reviews a single product, usually negatively to make its reputation slump. This study analyses the differences among legitimate users and ‘review bombers’, using common classifiers and techniques from spam detection to identify suspicious reviews, by looking at both content and user’s features.
2021
978-88-5518-340-6
review bomb; online ratings; cold start; machine learning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/511632
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