  Social Media usage has increased to an all-time high level in today's digital
world. The majority of the population uses social media tools (like Twitter,
Facebook, YouTube, etc.) to share their thoughts and experiences with the
community. Analysing the sentiments and opinions of the common public is very
important for both the government and the business people. This is the reason
behind the activeness of many media agencies during the election time for
performing various kinds of opinion polls. In this paper, we have worked
towards analysing the sentiments of the people of India during the Lok Sabha
election of 2019 using the Twitter data of that duration. We have built an
automatic tweet analyser using the Transfer Learning technique to handle the
unsupervised nature of this problem. We have used the Linear Support Vector
Classifiers method in our Machine Learning model, also, the Term Frequency
Inverse Document Frequency (TF-IDF) methodology for handling the textual data
of tweets. Further, we have increased the capability of the model to address
the sarcastic tweets posted by some of the users, which has not been yet
considered by the researchers in this domain.
