• P Sandhya Krishna
• R.VeeraBabu
• Othuri Soniya
• Garikapati Bhanu Teja
• Pasupuleti Rekha Madhuri , Javvaji Meghana

Human emotions can be shown in two ways: through words and without words. Speaking, making sounds, and writing are ways we use words to express ourselves. Without words, we use our faces and body movements to show how we feel. In our tech-filled world today most people around the globe like to use written words to share what they think or feel. They do this on social media and when they write reviews about things they buy online.Sentiment analysis looks at how people feel about things. It can examine tweets to understand public opinion on news, laws, social movements, and politicians. Sentiment analysis falls under both natural language processing and machine learning. It aims to separate, spot, or show views from different info sources like news, reviews, and articles. This method groups opinions as positive, neutral, happy, sad, shocked, or negative. Predicting election results from tweets in various Indian languages proves challenging.To grab tweets in Hindi, English, and Telugu, we used the Twitter Archiver program. We looked at the Kaggle data set online to mine text data. Emotion recognition is a system that has an impact on affective computing. It helps to spot and predict how people feel, like when they're angry, sad, or happy.

Text data, emotion detection, tokenization, Logistic Regression, SVM, Decision Tree

"EMOTION RECOGNITION USING TEXT-BASED ANALYSIS USING MACHINE LEARNING: A STUDY ON USER-GENERATED CONTENT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.256-265, November-2024, Available :http://www.jetir.org/papers/JETIRGO06025.pdf

"EMOTION RECOGNITION USING TEXT-BASED ANALYSIS USING MACHINE LEARNING: A STUDY ON USER-GENERATED CONTENT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. pp256-265, November-2024, Available at : http://www.jetir.org/papers/JETIRGO06025.pdf