• Venkata Rama Koundinya Lanka
• Rohit Chivukula
• Uday Syamala

Advancement of mobile and internet technology improves the communication and freedom of speaking in social networks, blogs and websites. Twitter is one of the most common and popular social media platforms gives freedom to the people to put their views, thoughts and opinion to the world. Analyzing large scale tweets by putting together large scale individual’s opinion on particular context will allows us to find various hidden topics and insights. This paper proposes for developing an automated topic modeling technique LDA to identify the interested topics of discussion from large scale tweets related to two famous political leaders of the country USA. Paper implements a topic modeling method on NLTK framework to analyse the tweets and project the most tweeted topics by both the politicians. Finally sentiment analysis of tweets is carried out using vader package. Results shows automated topic modeling and sentiment analysis of tweets in Python improves the speed, accuracy compare to normal R tool and visualization of data is better done in Python.

Twitter data analytics; LDA; NLTK; big data; sentiment analysis; topic modeling.

"Automated Topic Modeling and Sentiment Analysis of Tweets using Python", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.75-78, March-2019, Available :http://www.jetir.org/papers/JETIRAC06016.pdf

"Automated Topic Modeling and Sentiment Analysis of Tweets using Python", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp75-78, March-2019, Available at : http://www.jetir.org/papers/JETIRAC06016.pdf