Product and service reviews can markedly influence consumer purchase decisions, leading to financial gains or losses for businesses. Therefore, there is a growing interest towards techniques for bringing out reviews that could negatively or positively bias new customers. To this goal, we propose a visual analysis of reviews that enables quick elicitation of interesting patterns and singularities. The proposed approach is based on a theoretically sound framework, while its effectiveness and viability is demonstrated by its application to real data extracted from Tripadvisor and Booking.com.

Visual Detection Of Singularities In Review Platforms

M Petrocchi;A Spognardi
2015

Abstract

Product and service reviews can markedly influence consumer purchase decisions, leading to financial gains or losses for businesses. Therefore, there is a growing interest towards techniques for bringing out reviews that could negatively or positively bias new customers. To this goal, we propose a visual analysis of reviews that enables quick elicitation of interesting patterns and singularities. The proposed approach is based on a theoretically sound framework, while its effectiveness and viability is demonstrated by its application to real data extracted from Tripadvisor and Booking.com.
2015
Istituto di informatica e telematica - IIT
applied computing
Fake Detection
online reviews
Social Computing
visualization techniques
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/305182
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