Determinants of User Ratings in Online Business Rating Services

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• 作者：Syed A. Rahman (16)
  Tazin Afrin (16)
  Don Adjeroh (16)
  
  16. West Virginia University ; Morgantown ; WV ; 26506 ; USA
  
• 关键词：Review rating ; Weather ; Random forest ; Yelp ; Business rating
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：9021
• 期：1
• 页码：412-420
• 全文大小：918 KB
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• 作者单位：Social Computing, Behavioral-Cultural Modeling, and Prediction
• 丛书名：978-3-319-16267-6
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

We investigate the key determinants of user ratings in social media-based business rating services. Our hypothesis is that beyond factors internal to a user, external factors, such as the direct and indirect influence of other users, and environmental factors beyond the control of the user have a significant role in determining the actual rating assigned by a user for a given service. To test this hypothesis, we used data from Yelp, and attempted to predict user ratings on location-based services, in particular food and restaurant business. Our results show improved prediction performance over the baseline, with improved robustness to rating variability and rating sparsity.