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Applying Sentiment and Social Network Analysis in User Modeling

  • Mohammadreza Shams
  • Mohammadtaghi Saffar
  • Azadeh Shakery
  • Heshaam Faili
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7181)

Abstract

The idea of applying a conjunction of sentiment and social network analysis to improve the performance of applications has recently attracted attention of researchers. In widely used online shopping websites, customers can provide reviews about a product. Also a number of relations like friendship, trust and similarity between products or users are being formed. In this paper a combination of sentiment analysis and social network analysis is employed for extracting classification rules for each customer. These rules represent customers’ preferences for each cluster of products and can be seen as a user model. The combination helps the system to classify products based on customers’ interests. We compared the results of our proposed method with a baseline method with no social network analysis. The experiments on Amazon’s meta-data collection show improvements in the performance of the classification rules compared to the baseline method.

Keywords

sentiment analysis social network analysis graph clustering polarity classification user model 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Mohammadreza Shams
    • 1
  • Mohammadtaghi Saffar
    • 1
  • Azadeh Shakery
    • 1
  • Heshaam Faili
    • 1
  1. 1.School of Electrical and Computer Engineering, College of EngineeringUniversity of TehranTehranIran

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