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The emergence of social media data and sentiment analysis in election prediction

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Abstract

This work presents and assesses the power of various volumetric, sentiment, and social network approaches to predict crucial decisions from online social media platforms. The views of individuals play a vital role in the discovery of some critical decisions. Social media has become a well-known platform for voicing the feelings of the general population around the globe for almost decades. Sentiment analysis or opinion mining is a method that is used to mine the general population’s views or feelings. In this respect, the forecasting of election results is an application of sentiment analysis aimed at predicting the outcomes of an ongoing election by gauging the mood of the public through social media. This survey paper outlines the evaluation of sentiment analysis techniques and tries to edify the contribution of the researchers to predict election results through social media content. This paper also gives a review of studies that tried to infer the political stance of online users using social media platforms such as Facebook and Twitter. Besides, this paper highlights the research challenges associated with predicting election results and open issues related to sentiment analysis. Further, this paper also suggests some future directions in respective election prediction using social media content.

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Notes

  1. http://conceptnet.io/ (Last accessed on: 13 March 2020).

  2. https://blog.twitter.com/engineering/en_us/a/2013/new-tweets-per-second-record-and-how.html (Last accessed on: 20 Feb. 2020).

  3. https://blog.twitter.com/official/en_us/a/2014/the-2014-yearontwitter.html (Last accessed on: 20 Feb. 2020).

  4. https://twiplomacy.com/blog/twiplomacy-study-2018/ (Last accessed on: 17 Feb. 2020).

  5. https://bcw-global.com/ (Last accessed on: 17 Feb. 2020).

  6. “Pew Research Centre is a nonpartisan fact tank that informs the public about the issues, attitudes, and trends shaping the world. The research center conducts public opinion polling, demographic research, content analysis, and other data-driven social science research.”

    https://www.pewresearch.org/about/ (Last accessed on 17 Feb. 2020).

  7. https://www.journalism.org/2018/09/10/news-use-across-social-media-platforms-2018/pj_2018-09-10_social-media-news_0-04/ (Last accessed on: 17 Feb. 2020).

  8. https://datasift.com/ (Last accessed on: 13 March 2020).

  9. https://discovertext.com/solutions/ (Last accessed on: 13 March 2020).

  10. http://topsy.thisisthebrigade.com/ (Last accessed on: 13 March 2020).

  11. https://nodexl.com/ (Last accessed on: 13 March 2020).

  12. https://sentic.net/ (Last accessed on: 13 March 2020).

  13. http://sentistrength.wlv.ac.uk/#About (Last accessed on: 13 March 2020).

  14. “Real Clear Politics is website that calculate poll results.” https://www.realclearpolitics.com/ (Last accessed on 15 March 2020).

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  1. Department of Computer Science and Engineering, Dr B R Ambedkar National Institute of Technology, Jalandhar, India

    Priyavrat Chauhan, Nonita Sharma & Geeta Sikka

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Chauhan, P., Sharma, N. & Sikka, G. The emergence of social media data and sentiment analysis in election prediction. J Ambient Intell Human Comput 12, 2601–2627 (2021). https://doi.org/10.1007/s12652-020-02423-y

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