Online reviews provide users with the opportunity to rate various types of items such as 3 movies, music, and video games using a combination of numeric scores and textual com4 ments. The study proposes a novelmethod that applies statisticalmatching on network-based 5 covariates,with the aimto improve the estimation of the association betweenwords and highly 6 controversial items in online reviews. The application of this method on a sample of 40,665 7 items from the website Metacritic detects 218 highly controversial items. The application 8 supports the theory that controversies onMetacritic are driven with a sense of self-awareness 9 of participating of an online controversy (‘review bombing’). Typical controversial topics 10 (sexual identities, religious morality, politics) are associated with controversial reviews, too.

A network-based matching design for text mining of hyper-polarised online reviews

Cantone Giulio Giacomo;Tomaselli Venera
2024-01-01

Abstract

Online reviews provide users with the opportunity to rate various types of items such as 3 movies, music, and video games using a combination of numeric scores and textual com4 ments. The study proposes a novelmethod that applies statisticalmatching on network-based 5 covariates,with the aimto improve the estimation of the association betweenwords and highly 6 controversial items in online reviews. The application of this method on a sample of 40,665 7 items from the website Metacritic detects 218 highly controversial items. The application 8 supports the theory that controversies onMetacritic are driven with a sense of self-awareness 9 of participating of an online controversy (‘review bombing’). Typical controversial topics 10 (sexual identities, religious morality, politics) are associated with controversial reviews, too.
2024
Review bombing, Polarisation, Bipartite networks centrality, Statistica matching, Text mining
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/646589
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