Determining the Popularity of Political Parties Using Twitter Sentiment Analysis

Sharma, Sujeet and Shetty, Nisha P (2017) Determining the Popularity of Political Parties Using Twitter Sentiment Analysis. In: FICTA, 14/10/2017, Bhubaneswar, Odisha.

[img] PDF
907.pdf - Published Version
Restricted to Registered users only

Download (553kB) | Request a copy


With the advancement in the Internet Technology, many people have started connecting to social networking websites and are using these micro-blogging websites to publically share their views on various issues such as politics, celebrity or services like ecommerce. Twitter is one of those very popular micro-blogging website having 328 million of users around the world who posts 500 million of tweets per day to share their views. These tweets are rich source of opinionated USER GENERATED CONTENT (UGC) that can be used for effective studies and can produce beneficial results. In this research we have done Sentiment Analysis (SA) or Opinion Mining (OM) on user generated tweets to get the reviews about major political parties and then used three algorithms, Support Vector Machine(SVM), Naïve Bayes Classifier and k-Nearest-Neighbour(k-NN) to determine the polarity of the tweet as positive, neutral or negative and finally based on these polarities we made a prediction of which party is likely to perform more better in the upcoming election.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Sentiment Analysis, Opinion Mining, Tokenization, Classification, natural language processing(NLP).
Subjects: Engineering > MIT Manipal > Information and Communication Technology
Depositing User: MIT Library
Date Deposited: 11 Feb 2019 04:33
Last Modified: 11 Feb 2019 04:33

Actions (login required)

View Item View Item