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Determinants of User Ratings in Online Business Rating Services

Part of the Lecture Notes in Computer Science book series (LNISA,volume 9021)

Abstract

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.

Keywords

  • Review rating
  • Weather
  • Random forest
  • Yelp
  • Business rating

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Correspondence to Don Adjeroh .

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Rahman, S.A., Afrin, T., Adjeroh, D. (2015). Determinants of User Ratings in Online Business Rating Services. In: Agarwal, N., Xu, K., Osgood, N. (eds) Social Computing, Behavioral-Cultural Modeling, and Prediction. SBP 2015. Lecture Notes in Computer Science(), vol 9021. Springer, Cham. https://doi.org/10.1007/978-3-319-16268-3_52

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  • DOI: https://doi.org/10.1007/978-3-319-16268-3_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16267-6

  • Online ISBN: 978-3-319-16268-3

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