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https://github.com/aditeyabaral/lok-sabha-election-twitter-analysis
Twitter Feeds were analysed during the Lok Sabha Elections 2019 to guage the overall popularities of each party and predict the winner based solely on the tweets made by the population. This was made as a part of our Data Science course (UE18CS203) at PES University.
https://github.com/aditeyabaral/lok-sabha-election-twitter-analysis
data-analysis data-science data-visualization elections loksabha nlp prediction probabilistic-graphical-models probability python python3 sentiment-analysis sentiment-classification sentiment-polarity sentiment-scores social-media socialmediaanalytics statistical-analysis statistical-models twitter
Last synced: about 1 month ago
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Twitter Feeds were analysed during the Lok Sabha Elections 2019 to guage the overall popularities of each party and predict the winner based solely on the tweets made by the population. This was made as a part of our Data Science course (UE18CS203) at PES University.
- Host: GitHub
- URL: https://github.com/aditeyabaral/lok-sabha-election-twitter-analysis
- Owner: aditeyabaral
- Created: 2019-12-16T13:57:27.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2019-12-16T14:40:30.000Z (about 5 years ago)
- Last Synced: 2023-03-06T09:33:21.510Z (almost 2 years ago)
- Topics: data-analysis, data-science, data-visualization, elections, loksabha, nlp, prediction, probabilistic-graphical-models, probability, python, python3, sentiment-analysis, sentiment-classification, sentiment-polarity, sentiment-scores, social-media, socialmediaanalytics, statistical-analysis, statistical-models, twitter
- Language: Jupyter Notebook
- Homepage:
- Size: 59.3 MB
- Stars: 5
- Watchers: 2
- Forks: 1
- Open Issues: 0