A quality-aware model for sales prediction using reviews

Authors:
Xiaohui Yu;Yang Liu;Xiangji Huang;Aijun An
Affiliations:
York University, Toronto, ON, Canada and Shandong University, Shandong, China;Shandong University, Jinan, China and York University, Toronto, ON, Canada;York University, Toronto, ON, Canada;York University, Toronto, ON, Canada
Venue:
Proceedings of the 19th international conference on World wide web
Year:
2010

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Abstract

Writing and publishing reviews online has become an increasingly popular way for people to express opinions and sentiments. Analyzing the large volume of online reviews available can produce useful knowledge that are of interest to vendors and other parties. Prior studies in the literature have shown that online reviews have a significant correlation with the sales of products, and therefore mining the reviews could help predict the sales performance of relevant products. However, those studies fail to consider one important factor that may significantly affect the accuracy of the prediction, i.e., the quality of the reviews. In this paper, we propose a regression model that explicitly takes into account the quality factor, and discusses how this quality information can be predicted when it is not readily available. Experimental results on a movie review dataset confirm the effectiveness of the proposed model.