Twitter-based sentiment analysis on Russia-Ukraine war

Massive news streams and several Online Social Networks (OSN), such as Twitter today necessitate automated analysis. But the majority of them don't offer sentiment analysis. The primary issue with news sentiment analysis is the disparity in reader and writer opinions toward the news text. News might be positive or negative, but it must be presented as simple facts in impartial language. The issue of sentiment analysis in OSN is still a real challenge because the most recent news has an impact on people's lives every day, despite the fact that there exist programs for sentiment analysis of news. Immediately following the report of a potential Russian invasion of Ukraine, OSN users from all over the world began to flood Twitter with tweets. We can better comprehend public opinion on various events before and during the war by analyzing these opinions. For sentiment analysis, 10009 distinct tweets from January 2022 to the third week of July 2022 were examined. We investigated the problem of sentiment analysis for Ukrainian and Russian news in this paper, created a corpus of Ukrainian and Russian news, and annotated each text with one of three categories: positive, negative, or neutral. Overall, 37.06 percent of tweets are positive, 22.90 percent are negative, and 39.5 percent are neutral.