Improving Opinion Spam Detection by Cumulative Relative Frequency Distribution [article]

Michela Fazzolari and Francesco Buccafurri and Gianluca Lax and Marinella Petrocchi
2020 arXiv   pre-print
Over the last years, online reviews became very important since they can influence the purchase decision of consumers and the reputation of businesses, therefore, the practice of writing fake reviews can have severe consequences on customers and service providers. Various approaches have been proposed for detecting opinion spam in online reviews, especially based on supervised classifiers. In this contribution, we start from a set of effective features used for classifying opinion spam and we
more » ... -engineered them, by considering the Cumulative Relative Frequency Distribution of each feature. By an experimental evaluation carried out on real data from Yelp.com, we show that the use of the distributional features is able to improve the performances of classifiers.
arXiv:2012.13905v1 fatcat:ht2hc76gubb4xbqtln2uia3qla