Analyzing the online public sentiments related to Russia-Ukraine war over Twitter
Abstract
Purpose
Sharing and obtaining information over social media has enabled people to express their opinions regarding any event. Since the tweets regarding the Russia-Ukraine war were extensively publicized on social media, this study aims to analyse the temporal sentiments people express through tweets related to the war.
Design/methodology/approach
Relevant hashtag related to the Russia-Ukraine war was identified, and tweets were downloaded using Twitter API, which were later migrated to Orange Data mining software. Pre-processing techniques like transformation, tokenization, and filtering were applied to the extracted tweets. VADER (Valence Aware Dictionary for Sentiment Reasoning) sentiment analysis module of Orange software was used to categorize tweets into positive, negative and neutral ones based on the tweet polarity. For ascertaining the key and co-occurring terms and phrases in tweets and also to visualize the keyword clusters, VOSviewer, a data visualization software, was made use of.
Findings
An increase in the number of tweets is witnessed in the initial days, while a decline is observed over time. Most tweets are negative in nature, followed by positive and neutral ones. It is also ascertained that tweets from verified accounts are more impactful than unverified ones. russiaukrainewar, ukraine, russia, false, war, nato, zelensky and stoprussia are the dominant co-occurring keywords. Ukraine, Russia and Putin are the top hashtags for sentiment representation. India, the USA and the UK contribute the highest tweets.
Originality/value
The study tries to explore the public sentiments expressed over Twitter related to Russia-Ukraine war.
Keywords
Acknowledgements
Conflict of interest: The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this study.
Funding: The authors received no financial support for the research, authorship and/or publication of this study.
Citation
Gulzar, R., Gul, S., Verma, M.K., Darzi, M.A., Gulzar, F. and Shueb, S. (2023), "Analyzing the online public sentiments related to Russia-Ukraine war over Twitter", Global Knowledge, Memory and Communication, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/GKMC-03-2023-0106
Publisher
:Emerald Publishing Limited
Copyright © 2023, Emerald Publishing Limited