Sentiment Analysis in the IT Domain an Enhanced Approach to VADER Sentiment

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2018 by IJCTT Journal
Volume-59 Number-1
Year of Publication : 2018
Authors : Kiran Hegde, Aarush Gupta, Aparna George and Anudeep Dhonde
DOI :  10.14445/22312803/IJCTT-V59P103

MLA

Kiran Hegde, Aarush Gupta, Aparna George and Anudeep Dhonde "Sentiment Analysis in the IT Domain an Enhanced Approach to VADER Sentiment". International Journal of Computer Trends and Technology (IJCTT) V59(1):15-19, May 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract
Applying sentiment analysis in the IT domain requires several enhanced techniques over the conventional methods used for social media analysis, mainly due to the technical data involved as well as the purpose of the analysis. We take a deep-dive into these challenges and present a comparison of the results obtained over the two techniques (VADER analysis and our enhanced approach) along-with the interpretation of the enhanced results obtained through our approach in this paper. We will also give a description of the future enhancements to be implemented as a part of our current approach.

Reference
[1] C.J. Hutto, Eric Gilbert, VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text
[2] Oaindrila Das, Rakesh Chandra Balabantaray, Sentiment Analysis of Movie Reviews using POS tags and Term Frequencies
[3] Deepak Singh Tomar ,Pankaj Sharma , A Text Polarity Analysis Using Sentiwordnet Based an Algorithm
[4] Wei Yen Chong, Bhawani Selvaratnam, Lay-ki Soon,Natural Language Processing for Sentiment Analy-sis: An Exploratory Analysis on Tweets
[5] Monisha Kanakaraj, Ram Mohana Reddy Guddeti, NLP based sentiment analysis on twitter data using ensemble classifiers
[6] Deepak Kumar Yadav, Sampada Vishwas Massey, Senti-ment Analysis Based on Data Mining and Natural Lan-guage Processing

Keywords
data analytics, IT,natural language processing, opinionmining, sentiment analysis, VAD-ER sentiment,work logs, Remedy, Service Now, ITIL, Operations