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East Meets West: Sentiment Analysis for Election Prediction

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Modern Approaches in Machine Learning & Cognitive Science: A Walkthrough

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1027))

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Abstract

There has been an exponential growth of social media in the recent past. Social media has provided the common public a medium to voice their opinions freely. Twitter is amongst the most used social networks, especially when it comes to raising opinions regarding politics. Politics has been a fascinating subject to discuss for the common people for ages, but modern-day Twitter has become the new platform for these political discussions. The data generated from these discussions can be used to analyse many real-life scenarios. In this paper, we used Twitter data to analyse and predict the 2020 US elections. We extracted tweets featuring the two primary candidates of the election: Joe Biden and Donald J. Trump. We have extracted two sets of tweets; 1) tweets by American users and 2) tweets by Indian users; based on geopolitical location. Using python packages, we classified the tweets into five different emotions. We used sentiment analysis (VADER) algorithms to assign polarity to the tweets, which would later help us predict the outcome of the elections. We have also compared the opinions of two countries on the election results. The observations have been displayed using various visualization techniques.

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Acknowledgements

We would like to thank Mr. Prathamesh Churi and Mrs. Shweta Loonkar for their guidance and support during the completion of this research paper. We would also like to thank Miss Farah Kaskas for her help in obtaining the American tweets dataset.

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Authors and Affiliations

  1. Computer Engineering Department, Mukesh Patel School of Technology, Management, and Engineering, NMIMS University, Mumbai, India

    Swapnil Singh, Sanvika Singhania, Vedang Pandya, Adhyan Singal & Ameyaa Biwalkar

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  1. Swapnil Singh
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  2. Sanvika Singhania
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  3. Vedang Pandya
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  4. Adhyan Singal
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  5. Ameyaa Biwalkar
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Corresponding author

Correspondence to Swapnil Singh .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, CMR Institute of Technology, Hyderabad, India

    Vinit Kumar Gunjan

  2. Department of Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Singh, S., Singhania, S., Pandya, V., Singal, A., Biwalkar, A. (2022). East Meets West: Sentiment Analysis for Election Prediction. In: Gunjan, V.K., Zurada, J.M. (eds) Modern Approaches in Machine Learning & Cognitive Science: A Walkthrough. Studies in Computational Intelligence, vol 1027. Springer, Cham. https://doi.org/10.1007/978-3-030-96634-8_2

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