• Pinki Yadav
• Sanchita Rathi
• Daksh Malhotra
• Prateek Bansal

Social media as we know plays a vital role in influencing one's opinion and life. We are so wrapped in our virtual world that we want to confess and share every feeling of expression and knowledge through words or pictures and Twitter is one of those platforms that provide us the freedom of speech. In this paper, we are going to analyze the sentiments of such speeches using a support vector machine and random forest in python in a format that the tweets will be categorized in either positive, negative or neutral zones. Using the Django framework allowing us to quickly and efficiently create a quality Web application for both the front end and back end.

Twitter, Django, Random Forest, Support Vector Machine, Sentiment

"Twitter Sentiment Analyzer", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 12, page no.1300-1305, December-2020, Available :http://www.jetir.org/papers/JETIR2012168.pdf

"Twitter Sentiment Analyzer", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 12, page no. pp1300-1305, December-2020, Available at : http://www.jetir.org/papers/JETIR2012168.pdf