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Analyzing Political Sentiment Using Twitter Data

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Information and Communication Technology for Intelligent Systems

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 107))

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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Declaration

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.

Author information

Authors and Affiliations

  1. Simplex Infrastructures Ltd., Kolkata, India

    Rajesh Bose & Raktim Kumar Dey

  2. Brainware Group of Institutions, Kolkata, India

    Sandip Roy

  3. University of Kalyani, Kolkata, India

    Debabrata Sarddar

Authors
  1. Rajesh Bose
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  2. Raktim Kumar Dey
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  3. Sandip Roy
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  4. Debabrata Sarddar
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Corresponding author

Correspondence to Sandip Roy .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India

    Suresh Chandra Satapathy

  2. Sabar Institute of Technology, Gujarat Technological University, Ahmedabad, Gujarat, India

    Amit Joshi

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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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