Twittering Public Sentiments: A Predictive Analysis of Pre-Poll Twitter Popularity of Prime Ministerial Candidates for the Indian Elections 2014

© Media Watch 6 (2) 238-254, 2015
ISSN 0976-0911 e-ISSN 2249-8818
DOI: 10.15655/mw/2015/v6i2/65670
 

Twittering Public Sentiments: A Predictive Analysis of Pre-Poll Twitter Popularity of Prime Ministerial Candidates for the Indian Elections 2014

KALYANI SURESH & CHITRA RAMAKRISHNAN
Amrita Vishwa VidyaPeetham, Coimbatore, India
 
Abstract
Twitter is a useful tool for predicting election outcomes, effectively complementing traditional opinion polling. This study undertakes a volume, sentiment and engagement analysis for predicting the popularity of Prime Ministerial candidates on Twitter as a run-up to the Indian Elections 2014. The results from a survey of 2,37,639 pre-poll tweets finds tweet volume as a significant predictor of candidate vote share, and volume and sentiments as predictors for candidate engagement levels. Higher engagement rates evolve from the horizontality of conversations about the candidate, therefore indicating a high degree of interactivity, but do not translate into a higher vote share.
 
Keywords: Twitter analytics, Indian elections 2014, Modi, Kejriwal, Rahul Gandhi, sentiment analysis, twitter engagement rate
 
References
 
Ahmed, S., & Jaidka, K. (2013). Protests against #delhigangrape on Twitter: Analyzing India’s Arab Spring. eJournal of eDemocracy and Open Government, 5(1), 28-58. Retrieved from http://www.jedem.org
Asur, S., & Huberman, B. (2010). Predicting the future with social media. Proceedings of ACM International Conference on Web Intelligence (pp. 492-499). Toronto, Canada: IEEE. doi:10.1109/WI-IAT.2010.63
Bakliwal, A., Arora, P., Madhappan, S., Kapre, N., Singh, M., & Varma, V. (2012). Mining sentiments from tweets. Proceedings of 3rd Workshop on Computational Approaches to Subjetivity and Sentiment Analysis (WASSA 2012), in conjunction with Association of Computational Lingusitics (ACL 2012) (pp. 11-18). Jeju, Republic of Korea: Association for Computational Linguistics.
Barbera, P., & Rivero, G. (2014). Understanding the political representativeness of Twitter users. Social Science Computer Review. doi:10.1177/0894439314558836
Boucher, J., & Osgood, C. (1969). The Pollyanna Hypothesis. Journal of Verbal Learning and Verbal Behavior, 8(1), 1-8. doi:doi:10.1016/S0022-5371(69)80002-2
Ceron, A., Curini, L., Iacus, S. M., & Porro, G. (2012). Tweet your vote: How content analysis of social networks can improve our knowledge of citizen’s policy preferences. An application to Italy and France. Retrieved from http://www.sisp.it/files/papers/2012/andrea-ceron-luigi-curini-e-stefano-iacus-1414.pdf
Chung, J., & Mustafaraj, E. (2011). Can Collective Sentiment Expressed on Twitter Predict Political Elections? Proceedings of Twenty-fifth AAAI Conference on Artificial Intelligence. San Francisco, USA: AAAI Press. Retrieved from https://www.aaai.org/ocs/index.php/AAAI/AAAI11/paper/view/3549
CNN-IBN. (2014). IBN Live Elections Social Tracker. Retrieved from CNN-IBN Live: http://ibnlive.in.com/general-elections-2014/social-tracker/
Coggins, S. (2012, October 2). Twitter Metrics: Social Media Analytics (Web log Post). Retrieved from Vervely.com: http://vervely.com/twitter-metrics-social-media-analytics/2012/
Coviello, L., Sohn, Y., Kramer, A., Marlow, C., Franceschetti, M., & al., e. (2014). Detecting emotional contagion in massive social networks. PLoS ONE, 9(3). doi:10.1371/journal.pone.0090315
Dearing, J., & Rogers, E. (1988). Agenda-setting research: Where has it been, where is it going? Communication Yearbook, pp. 555-594.
ECI. (2014). ECI Main Page. Retrieved from ECI Web Site: eci.nic.in/eci_main1/index.aspx
Enjolras, B., Steen-Johnsen, K., & Wollebaek, D. (n.d.). How do social media change the conditions for civic and political mobilization. Retrieved from http://www.uio.no/english/research/interfaculty-research-areas/democracy/news-and-events/events/conferences/2012/papers-2012/steen-johnsen-elrojas-woolebaek-wshop%5D.pdf
Firstpost. (2014, May). Why FB, Twitter and Google are betting big on India’s Elections. Retrieved from Firstpost.com: http://www.firstpost.com/politics/why-fb-twitter-and-google-are-betting-big-on-indias-elections-1510215.html
Garcia, D., Garas, A., & Schweitzer, F. (2012, May 10). Emotional persistence in online chatting communities. Science Reports. doi:10.1038/srep00402
Gayo-Avello, D., Schoen, H., Metaxas, P., Mustafaraj, E., Strohmaier, M., & Gloor, P. (2013). The power of prediction with social media. Internet Research, 23(5), 528-543. doi:10.1108/IntR-06-2013-0115
Gnanasambandam, M; Madgavkar, A; Kaka, N; Manyika, J; Chui, M; Bughin, J; Gomes, M. (2013). Online and Upcoming: The Internet’s Impact on India. McKinsey & Company. Retrieved from http://www.mckinsey.com/search.aspx?q=Internet%27s+impact+on+India
Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91(3), 481-510. Retrieved from http://www.jstor.org/stable/2780199
Habermas, J. (1989). The Structural Transformation of the Public Sphere: An Inquiry into a category of Bourgeois Society. (T. Burger, Trans.) CC BY-SA 3.0. Retrieved from en.wikipedia.org
IAMAI. (2014). Internet in India 2014.. Retrieved from IAMAI: http://www.iamai.in/rsh_pay.aspx?rid=4hjkHu7GsUU=
India, E. (2014). Election India Opinion Polls. Retrieved from electionindia2014: http://electionindia2014.co.in
IRIS, & IAMAI. (2013). Social Media and Lok Sabha Elections. Retrieved from esocialsciences.org: http://www.esocialsciences.org/General/A2013412184534_19.pdf
Kelly, J., Barash, V., Alexanyan, K., Etling, B., Robert, G., & Palfrey, J. (2012). Mapping Russian Twitter. Berkman Center Research Publication(3). Retrieved from http://ssrn.com/abstract=2028158
Leavitt, A., Burchard, E., Fisher, D., & Gilbert, S. (2009). The influentials: New approaches for analyzing influence on twitter. Web Ecology Project, 4(2), 1-18. Retrieved from http://www.webecologyproject.org/2009/09/analyzing-influence-on-twitter/
Lilleker, D. (2006). Key Concepts in Political Communication. SAGE Publications.
McAdam, D., & Rucht, D. (1993). The Cross-national diffusion of movement ideas. The Annals of the American Academy of Political and Social Science, 528(1), 56-74. doi:10.1177/0002716293528001005
McCombs, M., & Shaw, D. (1972). The agenda-setting function of mass media. Public Opinion Quarterly, 36(2), 176-187. doi:10.1086/267990
Mehl, M. (2006). The lay assessment of subclinical depression in daily life. Psychological Assessment, 18, 340-345.
Metaxes, P., Mustafaraj, E., & Gayo-Avello, D. (2011). How (not) to predict elections. Proceedings of Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third International Conference on Social Computing (SocialCom) (pp. 165-171). Boston: IEEE Press. doi:10.1109/PASSAT/SocialCom.2011.98
Mitchell, A., & Hitlin, P. (2013). Twitter Reaction to Events often at Odds with Overall Public Opinion. Pew Research Centre. Retrieved from http://www.pewresearch.org/2013/03/04/twitter-reaction-to-events-often-at-odds-with-overall-public-opinion/
O’Connor, B., Balasubramanyan, R., Routledge, B. R., & Smith, N. (2010). From tweets to polls: Linking text sentiment to public opinion time series. Proceedings of the International AAAI Conference on Weblogs and Social Media (ICWSM 2010) (pp. 122-129). Washington, D.C: AAAI Press. Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/ICWSM10/paper/view/1536
Rogers, E. (1995). Diffusion of Innovations (Fourth Paperback ed.). New York: The Free Press Simon & Schuster Inc.
Sahin, I. (2006, Apr 3). Detailed review of Rogers’ diffusion of innovations theory and educational technology – related studies based on Roger’s theory. Turkish Online Journal of Educational Technology, 5(2), p. 1. Retrieved from http://eric.ed.gov/?q=technology+and+e ducation&ff1= souOnline+ Submission &id=ED501453
Sen, A. (2012). The social media as a public sphere: The rise of social opposition. Proceedings of the International Conference on Communication, Media, Technology and Design (pp. 490-494). Istanbul: ICCMTD.
Steffens, N., & Haslam, S. (2013). Power through ‘Us’: Leaders’ use of we-referencing language predicts election victory. PLoS ONE, 8(10). doi:10.1371/journal.pone.0077952
Stieglitz, S., & Dang-Xuan, L. (2012). Social media and political communication: A social media analytics framework. Social Network Analysis and Mining, 3(4), 1277-1291. Retrieved from http://dx.doi.org/10.1007/s13278-012-0079-3
Tham, J., & Zanuddin, H. (2013). Malaysia’s 13th general election: Political communication battle and public agenda in social media. Proceedings from the Conference Organized by Asian Network for Public Opinion Research. Seoul: ANPOR, p. 7. Retrieved from academia.edu: http://www.academia.edu/5433568/Malaysias_13th_General_Election_political_communication_battle_and_public_agenda_in_social_media
Toms, M. (2014, April 25). 20 million election tweets: India votes for Twitter. Hindustan Times. Retrieved from http://www.hindustantimes.com/business-news/20-million-election-tweets-india-votes-for-twitter/article1-1208135.aspx
Top Ten Indian Journalists to Follow on Twitter. (2013, July 30). Retrieved from Social Samosa: http://www.socialsamosa.com/2013/07/top-ten-indian-journalists-to-follow-on-twitter/
Tumasjan, A., Sprenger, T., Sandner, P., & Welpe, I. (2010). Predicting elections with Twitter: What 140 Characters Reveal about Political Sentiment. Proceedings of International AAAI Conference on Weblogs and Social Media; Fourth International AAAI Conference on Weblogs and Social Media. Washington: AAAI Press. Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/ICWSM10/paper/view/1441
Wu, M. (2012, March 19). Science of Social Blog.( p. 1). Retrieved from Lithium.com: http://community.lithium.com/t5/Science-of-Social-blog/Big-Data-Big-Prediction-Looking-through-the-Predictive-Window/ba-p/41068
Wu, S., Hofman, J., Mason, W., & Watts, D. (2011). Who says what to whom on Twitter. Proceedings of the 20th international conference on World wide web (pp. 705-714). Hyderabad: ACM.
Yoon, H., & Park, H. (2011). Social media information flow and public representation: A case of South Korean politicians on Twitter. Proceedings of the 9th International Triple Helix Conference. California: Triple Helix Association.
 
 
Dr. Kalyani Suresh is an assistant professor in the Department of Communication at Amrita Vishwa Vidyapeetham. Ettimadai, Coimbatore, India, She specializes in mediated communication, social media and youth studies.
Chitra Ramakrishnan is an assistant professor in the Department of Communication at Amrita Vishwa Vidya Peetham, Ettimadai, Coimbatore, India. Her current research interests include search marketing and data journalism.