Abstract
Today microblogging has become a very common platform for exchanging opinion among us. Many users exchange their thoughts on various aspects of their activity. Consequently, microblogging Web sites are the substantial origin of information for sentiment analysis and opinion mining. Twitter is a famous microblogging Web site where 500 million tweets are posted every day. In this manuscript, we summarize the data set of Twitter messages related to recent 14th Gujarat Legislative Assembly Election, 2017, for predicting the chances of winning party by utilizing public’s opinion. We use NRC Emotion Lexicon to determine the overall tone of the event by eight emotions. Furthermore, we use a deep learning tool named ParallelDots AI APIs by ParallelDots, Inc. that can analyze the sentiment into positive, negative, and neutral. This tool helped to extract various people’s sentiment and summarize the results for further decision making.
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The authors declare and solemnly affirm that this research has neither been funded by any political or religious groups nor are the authors in any way affiliated to any institutions with direct or indirect access to groups with biased interests. This research work has been carried out exclusively and independently by the authors in the interests of technology and progress of science in sentiment analysis and related fields.
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Bose, R., Dey, R.K., Roy, S., Sarddar, D. (2019). Analyzing Political Sentiment Using Twitter Data. In: Satapathy, S., Joshi, A. (eds) Information and Communication Technology for Intelligent Systems . Smart Innovation, Systems and Technologies, vol 107. Springer, Singapore. https://doi.org/10.1007/978-981-13-1747-7_41
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DOI: https://doi.org/10.1007/978-981-13-1747-7_41
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