Abstract
In the recent era, humans have become detached from their surroundings, immediate peers and more addicted to their social media platforms and micro-blogging sites. Technology is digitalizing at a very fast pace and this has led to man being social, but only on technological forefront. Social media platforms like twitter, facebook, whatsapp, instagram are in trend. In our paper, we will concentrate on data generated through Twitter (tweets). People express their opinions, perspectives within a 140 character tweet, which is subjective. We try to analyze their emotion by tweet classification followed by sentiment analysis. On an average, with 328 million Twitter users, 6000 tweets are generated every second. This tremendous amount of data can be used to assess general public’s views in economy, politics, environment, product reviews, feedbacks etc. and so many other sectors. Here, we take into account the political data from Tweets. The data obtained can be images, videos, links, emoticons, text, etc. The results obtained could help the government function better, improve their flaws, plan out better strategies to empower the nation.
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Patil, A.P., Doshi, D., Dalsaniya, D., Rashmi, B.S. (2018). Applying Machine Learning Techniques for Sentiment Analysis in the Case Study of Indian Politics. In: Thampi, S., Krishnan, S., Corchado Rodriguez, J., Das, S., Wozniak, M., Al-Jumeily, D. (eds) Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2017. Advances in Intelligent Systems and Computing, vol 678. Springer, Cham. https://doi.org/10.1007/978-3-319-67934-1_31
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DOI: https://doi.org/10.1007/978-3-319-67934-1_31
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