Twitter and elections: are tweets, predictive, reactive, or a form of buzz?

Information Communication and Society

Volumn 18, Issue 7, 2015, Pages 816-831

  Murthy, Dhiraj ^a  

^a UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

buzz; elections; political sentiment; Republican; social media; social media strategy; Twitter

Indexed keywords

EID: 84926256277     PISSN: 1369118X     EISSN: 14684462     Source Type: Journal    
DOI: 10.1080/1369118X.2015.1006659     Document Type: Article

References (53)

1. ABC News. (2011). @Jon2012Girls Talk Twitter, Politics & Dad. ABC News.
2. Ausserhofer, J., & Maireder, A. (2013). National politics on Twitter. Information, Communication & Society, 16(3), 291–314. doi: 10.1080/1369118X.2012.756050
3. Benamara, F., Cesarano, C., Picariello, A., Recupero, D. R., & Subrahmanian, V. S. (2007). Sentiment analysis: Adjectives and adverbs are better than adjectives alone. Proceedings of the International Conference on Weblogs and Social Media, Boulder, CO.
4. Bourdieu, P., & Passeron, J. C. (1977). Reproduction in education, society and culture. London: Sage.
5. Boykoff, J., & Laschever, E. (2011). The tea party movement, framing, and the US media. Social Movement Studies, 10(4), 341–366. doi: 10.1080/14742837.2011.614104
6. Burgess, J., & Green, J. (2009). YouTube: Online video and participatory culture. Cambridge: Polity Press.
7. Caldarelli, G., & Chessa, A., Pammolli, F., Pompa, G., Puliga, M., Riccaboni, M., & Riotta, G. (2014). A multi-level geographical study of Italian political elections from Twitter data. PloS one, 9(5), e95809. doi: 10.1371/journal.pone.0095809
8. Chung, J. E., & Mustafaraj, E. (2011). Can collective sentiment expressed on Twitter predict political elections? 25th AAAI Conference on Artificial Intelligence, San Francisco, CA.
9. Cillizza, C. (2012). South Carolina Republican Debate: Winners and losers. The Washington Post.
10. Cogburn, D. L., & Espinoza-Vasquez, F. K. (2011). From networked nominee to networked nation: Examining the impact of Web 2.0 and social media on political participation and civic engagement in the 2008 Obama campaign. Journal of Political Marketing, 10(1–2), 189–213. doi: 10.1080/15377857.2011.540224
11. Cohen, T. (2012). Santorum suspends campaign, clearing Romney's path. CNN. Retrieved May 8, 2012, from http://www.cnn.com/2012/04/10/politics/campaign-wrap/index.html
12. Conover, M. D., Ratkiewicz, J., Francisco, M., Goncalves, B., Menczer, F., & Flammini, A. (2011). Political polarization on Twitter. Proceedings of the ICWSM: Fifth International AAAI Conference on Weblogs and Social Media, Barcelona, Spain.
13. Daku, M., Soroka, S., & Young, L. (2011). Lexicoder. Montréal: McGill University. Retrieved from: http://www.lexicoder.com
14. Duggan, M., & Brenner, J. (2013). The demographics of social media users, 2012. Pew Research Center's Internet & American Life Project, Washington, DC.
15. Earl, J., & Kimport, K. (2011). Digitally enabled social change: Activism in the Internet age. Cambridge: MIT Press.
16. Fahrni, A., & Klenner, M. (2008). Old wine or warm beer: Target-specific sentiment analysis of adjectives.
17. Freeman, B., & Chapman, S. (2008). Gone viral? Heard the buzz? A guide for public health practitioners and researchers on how Web 2.0 can subvert advertising restrictions and spread health information. Journal of Epidemiology and Community Health, 62(9), 778–782. doi: 10.1136/jech.2008.073759
18. Gayo-Avello, D. (2012a). I wanted to predict elections with Twitter and all I got was this Lousy Paper – a Balanced Survey on election prediction using Twitter data. arXiv preprint arXiv:1204.6441.
19. Gayo-Avello, D. (2012b). No, You cannot predict elections with Twitter. Internet Computing, IEEE, 16(6), 91–94. doi: 10.1109/MIC.2012.137
20. González-Ibáñez, R., & Muresan, S., & Wacholder, N. (2011). Identifying sarcasm in Twitter: A closer look. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Short papers (Vol. 2). Association for Computational Linguistics, Portland, OR, pp. 581–586.
21. Hermida, A. (2010). From TV to Twitter: How ambient news became ambient journalism. M/C Journal, 13(2). Retrieved from: http://www.journal.media-culture.org.au/index.php/mcjournal/article/viewArticle/220%26gt
22. Hong, S., & Nadler, D. (2011). Does the early bird move the polls?: The use of the social media tool ‘Twitter’ by U.S. politicians and its impact on public opinion. Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times. College Park, Maryland, ACM, pp. 182–186.
23. Hong, S., & Nadler, D. (2012). Which candidates do the public discuss online in an election campaign?: The use of social media by 2012 presidential candidates and its impact on candidate salience. Government Information Quarterly, 29(4), 455–461. doi: 10.1016/j.giq.2012.06.004
24. Hsu, C.-l., & Park, H. W. (2011). Sociology of hyperlink networks of web 1.0, Web 2.0, and Twitter: A Case Study of South Korea. Social Science Computer Review, 29(3), 354–368. doi: 10.1177/0894439310382517
25. Jungherr, A., Jürgens, P., & Schoen, H. (2012). Why the pirate party won the German election of 2009 or the trouble with predictions: A response to Tumasjan, A., Sprenger, T. O., Sander, P. G., & Welpe, I. M. “Predicting elections with Twitter: What 140 characters reveal about political sentiment. Social Science Computer Review, 30(2), 229–234. doi: 10.1177/0894439311404119
26. Kim, M., & Park, H. (2012). Measuring Twitter-based political participation and deliberation in the South Korean context by using social network and Triple Helix indicators. Scientometrics, 90(1), 121–140. doi: 10.1007/s11192-011-0508-5
27. Kiss, J. (2010). Twitter election predictions are more accurate than YouGov. The Guardian. London.
28. Lassen, D. S., & Brown, A. R. (2011). Twitter: The electoral connection? Social Science Computer Review, 29, 419–436. doi: 10.1177/0894439310382749
29. Lin, C., & He, Y. (2009). Joint sentiment/topic model for sentiment analysis. Proceedings of the 18th ACM conference on Information and knowledge management. Hong Kong, China, ACM: 375–384.
30. Livne, A., Simmons, M. P., Adar, E., & Adamic, L. A. (2011). The party is over here: Structure and content in the 2010 election. Proceedings of the Proceedings of the International Conference on Weblogs and Social Media, Barcelona, Spain, pp. 17–21.
31. Mackowiak, M. (2011). Can we please stop talking about Huntsman? New York, National Review.
32. McLuhan, M. (2003). Understanding me: Lectures and interviews. Cambridge, MA: MIT Press.
33. Metaxas, P. T., Mustafaraj, E., & Gayo-Avello, D. (2011). How (Not) to predict elections. Privacy, Security, Risk and Trust (PASSAT) and 2011 IEEE Third Inernational Conference on Social Computing (SocialCom), Boston, MA.
34. Murthy, D. (2013). Twitter: Social communication in the Twitter age. Cambridge: Polity.
35. Orsini, L. R. (2011). @Jon2012girls: Huntsman's daughters outpoll GOP candidate father. The Daily Dot, Daily Dot LLC.
36. Postman, N. (2000). The humanism of media ecology. Proceedings of the Media Ecology Association (Vol. 1), Fordham University, New York, NY, pp. 10–16.
37. Qualman, E. (2011). Socialnomics: How social media transforms the way we live and do business. Hoboken, NJ: Wiley.
38. Ratkiewicz, J., Conover, M. D., Meiss, M., Gonçalves, B., Flammini, A., Menczer, F. (2011). Detecting and tracking political abuse in social media. Proceedings of the ICWSM: Fifth International AAAI Conference on Weblogs and Social Media, Barcelona, Spain.
39. Sakaria, A. K. H., Singer, M. D., & Uhrmacher, D. T. (2012). #140ToWinIt. Pitt Political Review, 8(2), 1–8. doi: 10.5195/ppr.2012.19
40. Skoric, M., Poor, N., Achananuparp, P., Lim, E.-P., & Jiang, J. (2012). Tweets and votes: A study of the 2011 Singapore general election. 2012 45th Hawaii International Conference on System Science (HICSS), Maui, HI.
41. Sonmez, F., Blake, A., Weiner, R., Jennings, N., & Zamora, A. (2012, January 21). Newt Gingrich wins South Carolina Republican primary. The Washington Post. Washington, DC. Retrieved from: http://www.washingtonpost.com/blogs/post-politics/post/republican-candidates-compete-in-michigan-and-arizona-live-primary-updates/2012/01/31/gIQAI9ofgR_blog.html
42. The Project for Excellence in Journalism. (2012). Social media users focus on Ron Paul. Washington, DC: Pew Research Center.
43. Tumasjan, A., Sprenger, T. O., Sandner, P. G., & Welpel, I. M. (2010). Predicting elections with Twitter: What 140 characters reveal about political sentiment. Proceedings of the ICWSM: Fourth International AAAI Conference on Weblogs and Social Media, Washington, DC.
44. Tumasjan, A., & Sprenger, T. O., Sandner, P. G., & Welpe, I. M. (2011). Election forecasts With Twitter: How 140 characters reflect the political landscape. Social Science Computer Review, 29(4), 402–418. doi: 10.1177/0894439310386557
45. Varnelis, K. (2008). Networked publics. Cambridge: MIT.
46. Vergeer, M., & Hermans, L., & Sams, S. (2013). Online social networks and micro-blogging in political campaigning: The exploration of a new campaign tool and a new campaign style. Party Politics, 19(3), 477–501. doi: 10.1177/1354068811407580
47. Whitelaw, C., Navendu, G., & Shlomo, A. (2005). Using appraisal groups for sentiment analysis. Proceedings of the 14th ACM Conference on Information and Knowledge Management, Bremen, Germany, pp. 625–631.
48. Williams, C. B., & Gulati, G. J. (2008, March). The political impact of Facebook: Evidence from the 2006 midterm elections and 2008 nomination contest. Politics & Technology Review, 1, 11–21.
49. Wilson, J. (2011). Playing with politics: Political fans and Twitter faking in post-broadcast democracy. Convergence: The International Journal of Research into New Media Technologies, 17(4), 445–461.
50. Young, L., & Soroka, S. (2012). Affective news: The automated coding of sentiment in political texts. Political Communication, 29(2), 205–231. doi: 10.1080/10584609.2012.671234
51. Yu, B., Kaufmann, S., & Diermeier, D. (2008). Exploring the characteristics of opinion expressions for political opinion classification. Proceedings of the 2008 International conference on Digital government research. Montreal, Canada, Digital Government Society of North America: 82–91.
52. Zarrella, D. (2009). The social media marketing book. Sebastopol, CA: O'Reilly Media.
53. Zeleny, J., & Parker, A. (2012). After ‘Oops’ in debate, Perry Says He'll stay in race. New York Times.