Sentiment Analysis on Large Scale Amazon Product Reviews

Authors

  • Sayyed Johar Dept. of CSE, JNNCE, Vishveshwariah Tecnlogligcal University Shivmaogga, Karnataka, India
  • Samara Mubeen Dept. of CSE, JNNCE, Vishveshwariah Tecnlogligcal University Shivmaogga, Karnataka, India

Keywords:

e-commerce, review of product, machine learning, supervised learning, Amazon dataset

Abstract

The world nowadays is becoming more digitalized. In this digitalized world e-commerce is taking the ascendancy by making products available within the reach of customers where the customer doesn’t have to go out of their house. As now a day’s people are relying on online products so the importance of a review is going higher. For selectng a product, a customer needs to go through thousands of reviews to understand a product. But in this prospering day of machine learning, going through thousands of reviews would be much easier if a model is used to polarize those reviews and learn from it. So by implementing supervised learning method on a large scale Amazon dataset to polarize it and get satisfactory accuracy.

 

References

Amandeep Kaur, DeepeshKhaneja ," Sentiment analysis on twitter using apache spark." International Conference on Computing, Communication and Automation (ICCCA), 2016., vol. 1, pp. 1–5 ,2016.

KuatYessenov, SasaMisailovi, “Sentiment Analysis in Movie Reviews comments." ." International Conference on Computer Science and Electronics Engineering (ICCSEE), vol. 1, no. 2, p. pp–72, 2009.

Han-xiaoshi,Xiao-jun “Sentiment Analysis in Hotel Reviews Based on Supervised Learning.” Internationals Conference on Machine Learning and Cybernetics ,2011.

Samha,Xu,Xia, Wong & Li “Opinion Annotation in Online Chinese Product Reviews.” In Proceedings of LREC conference, 2008.

T. U. Haque, N. N. Saber, and F. M. Shah, “Sentiment analysis on large scale Amazonpduct reviews,” 2018

S. Paknejad, “Sentiment classification on Amazon reviews using machine learning approaches,” 2018.

X. Fang and J. Zhan, “Sentiment analysis using product review data,” Journal of Big Data, vol. 2, no. 1, 2015. [Online]. [11] Z. Zhou and L. Xu, “Amazon Food Review Classification using Deep Learning and Recommender System,” Stanford University, 2009

J. Nowak, A. Taspinar, and R. Scherer, “LSTM recurrent neural networks for short text and sentiment classification,” Lecture Notes in Computer Science (including sub-series Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017.

KuatYessenov,“Sentiment Analysis on YouTube Movie Trailer comments to determine the impact on Box-Office Earning”,2016.

Su SuHtay, KhinThidar Lynn"Sentiment Analysis and Sentiment Classification of Amazon Product Reviews." Conference paper Swarthmore College, 2016.

“Amazon Reviews for Sentiment Analysis.” [Online]. https://www.kaggle.com/bittlingmayer/amazonreviews#train.ft.txt.bz2

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Published

2020-02-28

How to Cite

[1]
S. Johar and S. Mubeen, “Sentiment Analysis on Large Scale Amazon Product Reviews”, Int. J. Sci. Res. Comp. Sci. Eng., vol. 8, no. 1, pp. 7–15, Feb. 2020.

Issue

Vol. 8 No. 1 (2020): February

Section

Research Article

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