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Predicting Online Review Scores Across Reviewer Categories

In this paper, we propose and test an approach based on regression models, to predict the review score of an item, across different reviewer categories. The analysis is based on a public dataset with more than 2.5 million hotel reviews, belonging to five specific reviewers’ categories. We first compute the relation between the average scores associated with the different categories and generate the corresponding regression model. Then, the extracted model is used for prediction: given the average score of a hotel according to a reviewer category, it predicts the average score associated with another category.

International Conference on Intelligent Data Engineering and Automated Learning, Madrid, 2018

Autori esterni: 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: IDEAL2018exWWWJ.pdf

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