• Corpus ID: 63492100

SENTIMENT ANALYSIS OF ONLINE USER REVIEWS

@article{Kumari2016SENTIMENTAO,
  title={SENTIMENT ANALYSIS OF ONLINE USER REVIEWS},
  author={Divya Kumari and Himmat Singh and Aditya Kumar Mishra},
  journal={International Journal of Modern Trends in Engineering and Research},
  year={2016},
  volume={3}
}
The project aims to improve the existing methods that are being employed in the field of sentiment analysis of online user reviews. The proposed method is a dual training algorithm that analyses both the original and reversed training reviews in pairs for learning a sentiment analyzer. The algorithm, in addition to the positive and negative aspects of a review also recognizes the neutral aspect (a three-class classification). The model called dual sentiment analysis addresses the polarity shift… 
1 Citations

Arabic Opinion Mining Using Distributed Representations of Documents

  • A. El-Halees
  • Computer Science
    2017 Palestinian International Conference on Information and Communication Technology (PICICT)
  • 2017
TLDR
Distributed representations for Arabic opinion mining are used and it is found that, in all datasets and all methods used in this experiment, the distributed representations have better performance than bag-of-words representation.

References

SHOWING 1-4 OF 4 REFERENCES

Dual Sentiment Analysis: Considering Two Sides of One Review

TLDR
A novel data expansion technique is proposed by creating a sentiment-reversed review for each training and test review, and a corpus-based method is developed to construct a pseudo-antonym dictionary, which removes DSA's dependency on an external antonym dictionary for review reversion.

Review of Dual Sentiment Analysis

TLDR
Sentiment Analysis is the area of study that analyzes customer feedback, opinions, sentiments, evaluations, attitudes, and from written language to find the opinion sites and monitoring them on the web.

An Introduction to Logistic Regression Analysis and Reporting

Abstract The purpose of this article is to provide researchers, editors, and readers with a set of guidelines for what to expect in an article using logistic regression techniques. Tables, figures,

Review of dual sentiment analysis”, International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064

  • Index Copernicus Value
  • 2013