Making Sense of Tweets Using Sentiment Analysis on Closely Related Topics

Overview

Journal Soc Netw Anal Min

Date 2021 May 10

PMID 33968279

Citations 4

Authors

Sarvesh Bhatnagar

Nitin Choubey

Affiliations

Soon will be listed here.

Abstract

Microblogging has taken a considerable upturn in recent years, with the growth of microblogging websites like Twitter people have started to share more of their opinions about various pressing issues on such online social networks. A broader understanding of the domain in question is required to make an informed decision. With this motivation, our study focuses on finding overall sentiments of related topics with reference to a given topic. We propose an architecture that combines sentiment analysis and community detection to get an overall sentiment of related topics. We apply that model on the following topics: shopping, politics, covid19 and electric vehicles to understand emerging trends, issues and its possible marketing, business and political implications.

Citing Articles

A reliable sentiment analysis for classification of tweets in social networks.

AminiMotlagh M, Shahhoseini H, Fatehi N Soc Netw Anal Min. 2022; 13(1):7.

PMID: 36532862 PMC: 9742011. DOI: 10.1007/s13278-022-00998-2.

On the development of an information system for monitoring user opinion and its role for the public.

Karyukin V, Mutanov G, Mamykova Z, Nassimova G, Torekul S, Sundetova Z J Big Data. 2022; 9(1):110.

PMID: 36465138 PMC: 9684810. DOI: 10.1186/s40537-022-00660-w.

How Italy Tweeted about COVID-19: Detecting Reactions to the Pandemic from Social Media.

Lorenzoni V, Andreozzi G, Bazzani A, Casigliani V, Pirri S, Tavoschi L Int J Environ Res Public Health. 2022; 19(13).

PMID: 35805444 PMC: 9265594. DOI: 10.3390/ijerph19137785.

A deep dive into COVID-19-related messages on WhatsApp in Pakistan.

Javed R, Usama M, Iqbal W, Qadir J, Tyson G, Castro I Soc Netw Anal Min. 2021; 12(1):5.

PMID: 34804253 PMC: 8590927. DOI: 10.1007/s13278-021-00833-0.

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