Reza, Md MajidSingh, SatwinderKundra, HarishReza, Md Rashid2024-01-212024-08-142024-01-212024-08-142023-05-0397898119745402367337010.1007/978-981-19-7455-7_33https://kr.cup.edu.in/handle/32116/3922The usage of social media has increased exponentially these days. People worldwide are sharing their opinions on different platforms such as Twitter, personal blogs, Facebook, and other similar platforms. Twitter has grown in popularity as a platform for people to express their thoughts and opinions on many different topics. The data from Twitter about the Taliban has been examined in this research work, and various machine learning algorithms have been applied including SVM, LR, and random forest. Text sentiments have been captured via TextBlob. Among the machine learning models applied, SVM outperformed all other models and achieved an accuracy score of around 94% on the tweet dataset and logistic regression outperformed other models with an accuracy score of 83% on the news article dataset. � 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.en-USHashtagsMachine learningNLPSentiment analysisTextBlobTweetsConference paperhttps://link.springer.com/10.1007/978-981-19-7455-7_33