• Gagan Chaurasia
• Raj Paliwad
• Jai Chandwani
• Nishant Teli

Sentiment analysis is the process of identifying and extracting subjective information from text data,such as opinions, emotions, and attitudes. It is a subfield of natural language processing and has applications in various fields, such as marketing, customer service, and politics. Sentiment analysis techniques can be used to classify text data as positive, negative, or neutral, and to identify the underlying emotions and sentiments. The goal of sentiment analysis is to automate the process of understanding human emotions and opinions expressed in text data, which is becoming increasingly important in the age of social media and online communication. By analyzing large amounts of text data, sentiment analysis can help businesses and organizations to gain insights into customer preferences and sentiment, to improve their products and services, and to make better decisions based on customer feedback. Overall, sentiment analysis is a powerful tool for understanding and analyzing human emotions and opinions expressed in text data, and has numerous applications in business, politics, and social sciences.

Sentiment Analysis, NLTK, Machine learning, Data mining, Emotion, Social media

"Sentiment Analysis on Social Media", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.d27-d31, March-2024, Available :http://www.jetir.org/papers/JETIR2403304.pdf

"Sentiment Analysis on Social Media", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppd27-d31, March-2024, Available at : http://www.jetir.org/papers/JETIR2403304.pdf