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- Vol. 5 Issue 2
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Election Prediction using Machine Learning
Authors
1Assistant Professor, Computer Science and Engineering, Sanketika Vidya Parishad Engineering College, Visakhapatnam, Andhra Pradesh, India. 2,3,4,5 Student, Computer Science and Engineering, Sanketika Vidya Parishad Engineering College, Visakhapatnam, Andhra Pradesh, India.
Article Information
- Published In
- Volume 5, Issue 2 (2025)
- Published Online
- March-April 2025
- Pages
- 79-83
- Article Type
- Review Article
References
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[6] B. O’Connor, R. Balasubramanyan, B. R. Routledge, and N. A. Smith, “From tweets to polls: Linking text sentiment to public opinion time
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[7] E. Sang and J. Bos, “Predicting the 2011 Dutch senate election results with Twitter,” in Proc. Workshop Semantic Anal. Social Media,
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[9] K. Singhal, B. Agrawal, and N. Mittal, “Modeling Indian general elections: Sentiment analysis of political Twitter data,” in Information
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[10] N. Dwi Prasetyo and C. Hauff, “Twitter-based election prediction in the developing world,” in Proc. 26th ACM Conf. Hypertext Social
Media (HT), 2015, pp. 149–158.
[11] J. A. Ceron-Guzman and E. Leon-Guzman, “A sentiment analysis system of Spanish tweets and its application in Colombia 2014
presidential election,” in Proc. IEEE Int. Conf. Big Data Cloud Comput. (BDCloud), Social Comput. Netw. (SocialCom), Sustain. Comput.
Commun. (Sustain Com) (BDCloud-SocialCom-SustainCom), Oct. 2016, pp. 250–257.
[12] S. Rodríguez et al., “Forecasting the Chilean electoral year: Using Twit ter to predict the presidential elections of 2017,” in Social
Computing and Social Media. Technologies and Analytics (Lecture Notes in Com puter Science: Lecture Notes in Artificial Intelligence and
Lecture Notes in Bioinformatics). Cham, Switzerland: Springer, 2018, pp. 298–314.
[13] O. Oyebode and R. Orji, “Social media and sentiment analysis: The Nigeria presidential election 2019,” in Proc. IEEE 10th Annu. Inf.
Technol., Electron. Mobile Commun. Conf. (IEMCON), Oct. 2019, pp. 0140–0146.
[14] B. S. Bello, I. Inuwa-Dutse, and R. Heckel, “Social media campaign strategies: Analysis of the 2019 Nigerian elections,” in Proc. 6th Int.
Conf. Social Netw. Anal., Manage. Secur. (SNAMS), Oct. 2019, pp. 142–149.
[15] B. Heredia, J. D. Prusa, and T. M. Khoshgoftaar, “Social media for polling and predicting United States election outcome,” Social Netw.
Anal. Mining, vol. 8, no. 1, p. 48, Dec. 2018.
2016.
[2] P. L. Francia, “Free media and Twitter in the 2016 presidential election: The unconventional campaign of Donald Trump,” Social Sci.
Comput. Rev., vol. 36, no. 4, pp. 440–455, Aug. 2018.
[3] K. Brito, N. Paula, M. Fernandes, and S. Meira, “Social media and presidential campaigns–preliminary results of the 2018 Brazilian
presidential election,” in Proc. 20th Annu. Int. Conf. Digit. Government Res., Jun. 2019, pp. 332–341.
[4] S. Tilton, “Virtual polling data: A social network analysis on a student government election,” Webology, vol. 5, no. 4, pp. 1–8, 2008.
[5] A. Tumasjan, T. O. Sprenger, P. G. Sandner, and I. M. Welpe, “Predicting elections with Twitter: What 140 characters reveal about political
sentiment,” in Proc. 4th Int. AAAI Conf. Weblogs Social Media, 2010, pp. 1–8.
[6] B. O’Connor, R. Balasubramanyan, B. R. Routledge, and N. A. Smith, “From tweets to polls: Linking text sentiment to public opinion time
series,” in Proc. 4th Int. AAAI Conf. Weblogs Social Media, 2010, pp. 1–8.
[7] E. Sang and J. Bos, “Predicting the 2011 Dutch senate election results with Twitter,” in Proc. Workshop Semantic Anal. Social Media,
2012, pp. 53–60.
[8] A. Ceron, L. Curini, S. M. Iacus, and G. Porro, “Every tweet counts? How sentiment analysis of social media can improve our knowledge
of citizens’ political preferences with an application to Italy and France,” New Media Soc., vol. 16, no. 2, pp. 340–358, Mar. 2014.
[9] K. Singhal, B. Agrawal, and N. Mittal, “Modeling Indian general elections: Sentiment analysis of political Twitter data,” in Information
Systems Design and Intelligent Applications (Advances in Intelligent Systems and Computing). New Delhi, India: Springer, 2015.
[10] N. Dwi Prasetyo and C. Hauff, “Twitter-based election prediction in the developing world,” in Proc. 26th ACM Conf. Hypertext Social
Media (HT), 2015, pp. 149–158.
[11] J. A. Ceron-Guzman and E. Leon-Guzman, “A sentiment analysis system of Spanish tweets and its application in Colombia 2014
presidential election,” in Proc. IEEE Int. Conf. Big Data Cloud Comput. (BDCloud), Social Comput. Netw. (SocialCom), Sustain. Comput.
Commun. (Sustain Com) (BDCloud-SocialCom-SustainCom), Oct. 2016, pp. 250–257.
[12] S. Rodríguez et al., “Forecasting the Chilean electoral year: Using Twit ter to predict the presidential elections of 2017,” in Social
Computing and Social Media. Technologies and Analytics (Lecture Notes in Com puter Science: Lecture Notes in Artificial Intelligence and
Lecture Notes in Bioinformatics). Cham, Switzerland: Springer, 2018, pp. 298–314.
[13] O. Oyebode and R. Orji, “Social media and sentiment analysis: The Nigeria presidential election 2019,” in Proc. IEEE 10th Annu. Inf.
Technol., Electron. Mobile Commun. Conf. (IEMCON), Oct. 2019, pp. 0140–0146.
[14] B. S. Bello, I. Inuwa-Dutse, and R. Heckel, “Social media campaign strategies: Analysis of the 2019 Nigerian elections,” in Proc. 6th Int.
Conf. Social Netw. Anal., Manage. Secur. (SNAMS), Oct. 2019, pp. 142–149.
[15] B. Heredia, J. D. Prusa, and T. M. Khoshgoftaar, “Social media for polling and predicting United States election outcome,” Social Netw.
Anal. Mining, vol. 8, no. 1, p. 48, Dec. 2018.
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