• Dipanjali Digambar Chavare
• Prof V.D. Jadhav

Users of Twitter, one of the most well-known social networking platforms, are free to express their ideas, opinions, and feelings. These tweets are compiled and analyzed to get sentiment data regarding the terrorist assault in Uri. The present study gathers tweets on the Uri attack and examines their polarity and feelings. Tweets are mined for polarity and emotions using text mining techniques. Five thousand tweets are pre-processed and recoded to create a collection of frequently used words. Sentiment analysis is a machine learning technique that looks for positive or negative polarity in texts. By using text samples that represent a range of emotions, machine learning technology can be trained to automatically identify sentiment without the need for human intervention

twitter, text mining, Sentiment Analysis, Positive, Negative words.

"Sentiment Analysis of text using SVM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 12, page no.e686-e689, December-2023, Available :http://www.jetir.org/papers/JETIR2312484.pdf

"Sentiment Analysis of text using SVM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 12, page no. ppe686-e689, December-2023, Available at : http://www.jetir.org/papers/JETIR2312484.pdf