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Mining Implicit Data Association from Tripadvisor Hotel Reviews

In this paper, we analyse a dataset of hotel reviews. In details, we enrich the review dataset, by extracting additional features, consisting of information on the reviewers’ profiles and the reviewed hotels. We argue that the enriched data can gain insights on the factors that most influence consumers when composing reviews (e.g., if the appreciation for a certain kind of hotel is tied to specific users’ profiles). Thus, we apply statistical analyses to reveal if there are specific characteristics of reviewers (almost) always related to specific characteristics of hotels. Our experiments are carried out on a very large dataset, consisting of around 190k hotel reviews, collected from the Tripadvisor website.

Workshops of the EDBT/ICDT 2018 Joint Conference , Vienna, 2018

Autori esterni: Vittoria Cozza (Department of Information Engineering, University of Padua, Padua, Italy), Angelo Spognardi (Dipartimento di Informatica, Sapienza Università di Roma, Rome, Italy)
Autori IIT:

Tipo: Contributo in atti di convegno
Area di disciplina: Computer Science & Engineering

File: paper-09.pdf

Attività: Social Media Analysis
Bolle dell'informazione e rilevamento di falsi in rete