This paper is published in Volume-5, Issue-2, 2019
Area
Natural Language Processing
Author
Abhinav Garapati
Co-authors
Naveen Bora, Hanisha Balla, Mohan Sai
Org/Univ
Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, India
Pub. Date
20 March, 2019
Paper ID
V5I2-1301
Publisher
Keywords
NLP, Sentiment analysis, POS tagging, Rule based, SentiWordNet, SentiPhraseNet

Citationsacebook

IEEE
Abhinav Garapati, Naveen Bora, Hanisha Balla, Mohan Sai. SentiPhraseNet: An extended SentiWordNet approach for Telugu sentiment analysis, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Abhinav Garapati, Naveen Bora, Hanisha Balla, Mohan Sai (2019). SentiPhraseNet: An extended SentiWordNet approach for Telugu sentiment analysis. International Journal of Advance Research, Ideas and Innovations in Technology, 5(2) www.IJARIIT.com.

MLA
Abhinav Garapati, Naveen Bora, Hanisha Balla, Mohan Sai. "SentiPhraseNet: An extended SentiWordNet approach for Telugu sentiment analysis." International Journal of Advance Research, Ideas and Innovations in Technology 5.2 (2019). www.IJARIIT.com.

Abstract

Sentimental Analysis in English language is a relatively easier task to perform as it has a predefined set of rules followed and accepted universally. But, when it comes to Indian languages, there isn’t a benchmark dataset. Moreover, if a data set exists, it cannot be validated as a similar sentence may differ in the meaning as the regional languages are very unpredictable and have no proper rules. In this paper, we used a Rule-Based Approach to build SentiPhraseNet. Here, we obtained the sentiment using SentiPhraseNet and validated the results using ACTSA which is an annotated corpus data set.
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