• Mayur Mahajan
• Aditya Bhure
• Vijayraj Bhakare
• Sumeet Patil
• Sarita Patil

Nowadays, social media is getting more attention. Public and private opinions on a wide range of topics are constantly expressed and distributed via a variety of social media platforms. Twitter is one of the most prominent social networking platforms. Twitter provides businesses with a quick and effective approach to assess customers' viewpoints on issues that are crucial to market success. Creating a sentiment analysis programme is a method for computing consumer perceptions. This study describes the creation of a sentiment analysis that extracts a large number of tweets. Tweepy, numpy, pandas, textblob, and nltk are some of the Python modules utilised in this project. Results classify customers' perspective via tweets into positive and negative, which is represented in a pie chart and tabular form.

Python, Numpy, Tweepy, NLTK, Pandas

"Twitter Sentiment Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.d196-d201, May-2022, Available :http://www.jetir.org/papers/JETIR2205443.pdf

"Twitter Sentiment Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppd196-d201, May-2022, Available at : http://www.jetir.org/papers/JETIR2205443.pdf