Designing A Twitter Sentiment Analysis and Recommender System Using Machine Learning Techniques
Social media provides a platform where people from all around the globe are free to share
their views about a common topic. Twitter is one of the trending social media platform which offers an
effective way to analyse different perspectives and opinions of its users using different sentiment analysis
techniques. In this paper, we will discuss an application of sentiment analysis techniques on the dynamic
dataset of twitter as well as a pre-existing dataset from Kaggle. We segregate tweets as positive, negative
and neutral and also plot the graph of the places from where the tweets have been made on an Html page.
In the proposed system, a recommendation that once can follow and block has also been made based on
the number of negative tweets made by them. We realized that finding more negative tweets done by the
same person is significantly low which clearly shows the limitations of the current work.