UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 2
February-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2102076


Registration ID:
305651

Page Number

660-667

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Title

Evoking Emotions from Tweets: lexicon based method of Sentimental Analysis

Abstract

Abstract Twitter a micro-blogging platform has gained huge popularity for its instant and quick information diffusion feature. Marketers are increasingly using social media to disseminate information related to their products and promotions on the social media. The robust growth of banking sector and its convergence with the new technology has brought in the revolutions in the economy. The purpose of the study is to ascertain the sentiment of the customers of India’s leading private bank on the popular social media platform “Twitter”. The study collects 5000 recent tweets of hdfc bank from its customer care twitter handle. The article uses R software for analysis and R studio for graphical interface to perform NLP - sentiment analysis using the “syuzhet” package given by saif mohammad which is based on NRC lexicon. Findings of the study reveal that people have positive sentiment towards hdfc bank and customers trust the bank. The findings also reveal the presence of considerable negative sentiment and display of sadness emotion. Emotions of anticipation are also on the higher side which state that people have higher expectations from the bank and its products and services. The study provides insights to managers of hdfc bank by suggesting them to reduce negative sentiment and sadness emotions of the customers by handling issues and complaints more effectively and indulge more in promotional activities which could surprise and delight their customers since these emotions are on a lower score. The study also states its shortcomings and also hints future researchers by providing limitations and avenues of future research which is across platforms and sector.

Key Words

sentiment analysis, consumer engagement, Twitter, social media, Retweets, emotion, R software.

Cite This Article

"Evoking Emotions from Tweets: lexicon based method of Sentimental Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 2, page no.660-667, February-2021, Available :http://www.jetir.org/papers/JETIR2102076.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Evoking Emotions from Tweets: lexicon based method of Sentimental Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 2, page no. pp660-667, February-2021, Available at : http://www.jetir.org/papers/JETIR2102076.pdf

Publication Details

Published Paper ID: JETIR2102076
Registration ID: 305651
Published In: Volume 8 | Issue 2 | Year February-2021
DOI (Digital Object Identifier):
Page No: 660-667
Country: Vijayapura, Karnataka, India .
Area: Management
ISSN Number: 2349-5162
Publisher: IJ Publication


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