Paper Title
Sentiment Analysis of Indian Election Tweets Using TextBlob and Machine Learning
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Registration ID: IJNRD_323478
Published ID: IJNRDK001030
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Sentiment Analysis of Indian Election Tweets Using TextBlob and Machine Learning
Abstract
Public opinion now grows differently because of social media - particularly when votes are coming up. Many social media platforms are available for users to post live updates about big and important events. One of these platforms (Twitter) has a feature that allows users to post a tweet (which includes short, real-time updates) about everything happening, especially during a big event such as an election. For example, a Twitter user may live tweet about candidates running in the election until the election is finished. We studied comments made by two high-profile Indian politicians (Narendra Modi (Prime Minister) and Rahul Gandhi). Our goal was to determine public sentiment toward them and how the public viewed their comments (positively, negatively, or neutrally). We used two separate methodologies to assess public sentiment toward the two politicians. One methodology is using traditional methods (statistical) to score each comment based on emotional sentiment (TextBlob). The other methodology is to create a measure of sentimental comments by looking for patterns in the comment stream, then compare those patterns to known examples in the real world of sentiment analysis (TF- IDF/LR). Prior to analysis, we removed any hyperlinks, tags, usernames, or unusual characters that appeared in the comment section. What stayed behind mattered most - the core message stripped bare but clear. Accuracy numbers told part of the story; full reports gave more depth. Confusion matrices showed where guesses went right or wrong. Visuals like pies and bars turned raw counts into something eyes could follow easily. Not every method worked equally well in practice. Learning from data beat looking up words when judging online feelings.
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How To Cite (APA)
Ancy Megona. A & Dr. S. Mangayarkarasi (May-2026). Sentiment Analysis of Indian Election Tweets Using TextBlob and Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(5), 172-178. https://ijnrd.org/papers/IJNRDK001030.pdf
Issue
Volume 11 Issue 5, May-2026
Pages : 172-178
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Paper Reg. ID: IJNRD_323478
Published Paper Id: IJNRDK001030
Research Area: Other area not in list
Author Type: Indian Author
Country: -, -, India
Published Paper PDF: https://ijnrd.org/papers/IJNRDK001030.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRDK001030
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