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Publication Details

Central University of Tamil Nadu 
Bonta Venkateswarlu, and Nandhini Kumaresh and N. Janardhan.  
Corresponding Authors:
DOI #:
Not Applicable 
A Comprehensive Study on Lexicon Based Approaches for Sentiment Analysis 
Asian Journal of Computer Science and Technology 
Sentiment Analysis, Opinion Mining, Sentiwordnet, NLTK, Text blob, VADER 
In recent years, it is seen that the opinion-based postings in social media are helping to reshape business and public sentiments, and emotions have an impact on our social and political systems. Opinions are central to mostly all human activities as they are the key influencers of our behaviour. Whenever we need to make a decision, we generally want to know others opinion. Every organization and business always wants to find customer or public opinion about their products and services. Thus, it is necessary to grab and study the opinions on the Web. However, finding and monitoring sites on the web and distilling the reviews remains a big task because each site typically contains a huge volume of opinion text and the average human reader will have difficulty in identifying the polarity of each review and summarizing the opinions in them. Hence, it needs the automated sentiment analysis to find the polarity score and classify the reviews as positive or negative. This article uses NLTK, Text blob and VADER Sentiment analysis tool to classify the movie reviews which are downloaded from the website www.rottentomatoes. com that is provided by the Cornell University, and makes a comparison on these tools to find the efficient one for sentiment classification. The experimental results of this work confirm that VADER outperforms the Text blob. 
Entered by:
Nandhini K on 2020-09-03 
It has always been the basic tenet of the Government of India, in generously funding R&D efforts at academic institutions over the years, that facilities established through such support be made available to those needing them and qualified to make use of them for their own research work

However, this was never easy or straightforward for, among other reasons, there was no ready source of information of what facility was available and where. Thanks to the Web, it is much easier today to have a national and regional “inventory of resources”, so as to match users with the resources they need, and to do all this in an efficient and transparent manner.

This can lead to a leap in R&D productivity and greatly enhance the effectiveness of public investment. This is the motivation behind I-STEM.
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