Contextual Sentiment Analysis Using Latent Semantic Indexing

Authors

  • S.Vijaya Assistant Professor Department of Information Technology, KG College of Arts and Science, Saravanampatty.

Keywords:

Opinions, Positive, Negative, Sentiment Analysis, Contextual Sentiment Analysis

Abstract

Generally people share their opinions in all aspects. These opinions and ideas may be used for to enhance the
business, improve a product, and so on. The upsurge of Web 2.0 has led maximum of these kind of opinion shared in
Blogs, Twitters, Face book and so on. These data can be taken for analysis to find out the nature of the opinion like
positive, negative or neutral. To analyze these opinions computational treatment of the opinions, sentiments and bias
of text which is known as Sentiment Analysis need to be performed. Sentiment Analysis is also known as Opinion
Mining. In general, keywords based variations are used to extract the sentiments. In case of the sentences bearing
implicit sentiments, the efficiency of this method becomes very less as finding implicit sentiments are difficult in this
kind of approach. Comparatively, Latent Sentiment Analysis with SVD improves the efficiency of Contextual based
Sentiment Analysis in great manner.

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Published

2019-03-31

How to Cite

S.Vijaya. (2019). Contextual Sentiment Analysis Using Latent Semantic Indexing. International Journal of Technical Innovation in Modern Engineering & Science, 5(18), -. Retrieved from https://ijtimes.com/index.php/ijtimes/article/view/3217

Issue

Vol. 5 No. 18 (2019): ICRESET-2019 (International Conference on Recent Explorations in Science, Engineering and Technologies)

Section

Articles