Research Article
IGSentiment Analysis of Russia and Ukraine War on Twitter Data: Using Azure Machin Learning and Deep Learning
@INPROCEEDINGS{10.1007/978-3-031-66044-3_8, author={Bhagirathi Nayak and Pritidhara Hota and Sunil Kumar Mishra}, title={IGSentiment Analysis of Russia and Ukraine War on Twitter Data: Using Azure Machin Learning and Deep Learning}, proceedings={Pervasive Knowledge and Collective Intelligence on Web and Social Media. Second EAI International Conference, PerSOM 2023, Hyderabad, India, November 24--25, 2023, Proceedings}, proceedings_a={PERSOM}, year={2024}, month={8}, keywords={Twitter Machine Learning Deep Learning Azure Sentiments}, doi={10.1007/978-3-031-66044-3_8} }- Bhagirathi Nayak
Pritidhara Hota
Sunil Kumar Mishra
Year: 2024
IGSentiment Analysis of Russia and Ukraine War on Twitter Data: Using Azure Machin Learning and Deep Learning
PERSOM
Springer
DOI: 10.1007/978-3-031-66044-3_8
Abstract
Facebook, Twitter, and other social media sites have become popular places for people to connect and air their views on many topics. The importance of employing machine learning methods for sentiment analysis or opinion mining of these posts cannot be overstated. Russia-Ukraine conflict, users from all around the world descended upon the site to share their thoughts. By analyzing these comments, we may get a sense of how the general population felt about various events leading up to and during the conflict. This paper is mostly focused on tweet data in two steps on the Russia-Ukraine conflict. First, we collected 47885 tweet data to retrieve and analyze the tweets that reflected the proportion of positive, neutral, and negative categories-based sentiments using Azure Machine Learning, after that, we used Deep Learning for the segmentation of sentiments with scores. Finally, we got positive: 18846, negative: 12751, neutral: 16288.
