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The impact of text preprocessing on the prediction of review ratings

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The impact of text preprocessing on the prediction of review ratings.pdf (151.6Kb)
Date
2020
Author
Işık, Muhittin
Daǧ, Hasan
Abstract
With the increase of e-commerce platforms and online applications, businessmen are looking to have a rating and review system through which they can easily reveal the feelings of customers related to their products and services. It is undeniable from the statistics that online ratings and reviews attract new customers as well as increase sales by means of providing confidence, ratification, opinions, comparisons, merchant credibility, etc. Although considerable research has been devoted to the sentiment analysis for review classification, rather less attention has been paid to the text preprocessing which is a crucial step in opinion mining especially if convenient preprocessing strategies are found out to increase the classification accuracy. In this paper, we concentrate on the impact of simple text preprocessing decisions in order to predict fine-grained review rating stars whereas the majority of previous work focused on the binary distinction of positive vs. negative. Therefore, the aim of this research is to analyze preprocessing techniques and their influence, at the same time explain the interesting observations and results on the performance of a five-class-based review rating classifier.

Source

Turkish Journal of Electrical Engineering and Computer Sciences

Issue

3

Volume

28

Pages

1405-1421

URI

https://doi.org/10.3906/elk-1907-46
https://hdl.handle.net/20.500.12469/2882

Collections

  • Araştırma Çıktıları / Scopus [1565]
  • Araştırma Çıktıları / TR Dizin [331]
  • Araştırma Çıktıları / WOS [1518]
  • Yönetim Bilişim Sistemleri / Management Information Systems [145]

Keywords

Text preprocessing
Sentiment analysis
Opinion mining
Review rating
Text mining

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DSpace software copyright © 2002-2015  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV