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Mining Worse and Better Opinions. Unsupervised and Agnostic Aggregation of Online Reviews

Abstract · Apr 18, 2017 15:20 ·

opinions mining worse review agnostic aggregation reviews online opinion terminology cs-si cs-cl cs-ir

Arxiv Abstract

  • Michela Fazzolari
  • Marinella Petrocchi
  • Alessandro Tommasi
  • Cesare Zavattari

In this paper, we propose a novel approach for aggregating online reviews, according to the opinions they express. Our methodology is unsupervised - due to the fact that it does not rely on pre-labeled reviews - and it is agnostic - since it does not make any assumption about the domain or the language of the review content. We measure the adherence of a review content to the domain terminology extracted from a review set. First, we demonstrate the informativeness of the adherence metric with respect to the score associated with a review. Then, we exploit the metric values to group reviews, according to the opinions they express. Our experimental campaign has been carried out on two large datasets collected from Booking and Amazon, respectively.

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