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Analysis of Consumer Reviews by Machine Learning Techniques

  • Sourav SinhaEmail author
  • M. Sandhya
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 39)

Abstract

The dynamic change in the usage of digital economy had drifted the customers towards using online shopping websites for their day to day purchase. Under such circumstances, customer reviews and ratings had been used by these online stores to generate trustworthy and esteemed brand in the digital market. Most of these reviews were unstructured text which had been widely used for sentiment analysis. This paper discusses about various machine learning algorithms proposed by different researchers to analyze the consumer reviews. Based on the existing work, we categorized three broad aspects in consumer reviews namely opinion mining, spam or fake review detection, collaborative filtering. In future work, we plan to propose customer review-oriented decision support system (CRDSS) which can help in consumer decision making process and thus improve the customer review helpfulness and rating prediction.

Keywords

eCommerce Consumer review Sentiment analysis Machine learning 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringB. S. Abdur Rahman Crescent Institute of Science and TechnologyChennaiIndia

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