• Rayees Ahmad
• yasmin shaikh
• sanjay tanwani

Social media platforms and Microblogging sites can be used to gather public opinion and sentiment on a range of topics, including the current state of affairs in war-torn countries. During a crisis, Online Social Networks (OSNs) play a critical role in information sharing. The information gathered during such a crisis, public opinion and sentiments on a large scale can be reflected. Twitter, in particular, contains a significant quantity of geo tagged tweets, allowing for sentiment analysis over time and geography. The primary goal of this research study is to harness the power of social media to monitor, examine, and analyze public opinion on a recent “Russia’s Invasion on Ukraine”, as public opinion is crucial in forming government policy. By delving deeper into social media, one may readily study people's behavior on a variety of subjects and policies, which would be impossible to do otherwise using traditional sources. In this research paper, it is aimed to classify the viewpoint as Positive, Negative, or Neutral by using Artificial Intelligence (AI) and Natural Language Processing (NLP). The findings of this study can assist various organizations and stockholders in improving their political strategies and commercial decision-making for current and future intents by utilizing social media networks as a valuable source of knowledge.

Sentiment Analysis, Natural Language Processing, Machine Learning, Twitter, Ukraine, Russia, Political reviews

""To Stand with Ukraine is to Stand with Humanity”: Sentiment Analysis using Machine Learning with NLP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.a804-a815, September-2022, Available :http://www.jetir.org/papers/JETIR2209086.pdf

""To Stand with Ukraine is to Stand with Humanity”: Sentiment Analysis using Machine Learning with NLP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. ppa804-a815, September-2022, Available at : http://www.jetir.org/papers/JETIR2209086.pdf