Advertisement

Analyzing polarization of social media users and news sites during political campaigns

  • Fabrizio Marozzo
  • Alessandro Bessi
Original Article

Abstract

Social media analysis is a fast growing research area aimed at extracting useful information from social networks. Recent years have seen a great interest from academic and business world in using social media to measure public opinion. This paper presents a methodology aimed at discovering the behavior of social network users and how news sites are used during political campaigns characterized by the rivalry of different factions. As a case study, we present an analysis on the constitutional referendum that was held in Italy on December 4, 2016. A first goal of the analysis was to study how Twitter users expressed their voting intentions about the referendum in the weeks before the voting day, so as to understand how the voting trends have evolved before the vote, e.g., if there have been changes in the voting intentions. According to our study, 48% of Twitter users were polarized toward no, 25% toward yes, and 27% had a neutral behavior. A second goal was to understand the effects of news sites on the referendum campaign. The analysis has shown that some news sites had a strong polarization toward yes (unita.tv, ilsole24ore.it and linkiesta.it), some others had a neutral position (lastampa.it, corriere.it, huffingtonpost.it and repubblica.it) and others were oriented toward no (ilfattoquotidiano.it, ilgiornale.it and beppegrillo.it).

Keywords

Social media analysis Public opinion Online information News sites Users’ polarization Social networks Political events 

References

  1. Anstead N, O’Loughlin B (2015) Social media analysis and public opinion: the 2010 UK general election. J Comput Mediat Commun 20(2):204–220.  https://doi.org/10.1111/jcc4.12102 CrossRefGoogle Scholar
  2. Belcastro L, Marozzo F, Talia D, Trunfio P (2017) Big data analysis on clouds. In: Sakr S, Zomaya A (eds) Handbook of big data technologies. Springer, Berlin, pp 101–142.  https://doi.org/10.1007/978-3-319-49340-4_4 ISBN: 978-3-319-49339-8CrossRefGoogle Scholar
  3. Bessi A, Coletto M, Davidescu GA, Scala A, Caldarelli G, Quattrociocchi W (2015) Science versus conspiracy: collective narratives in the age of misinformation. PloS One 10(2):e0118093CrossRefGoogle Scholar
  4. Breiman L (2001) Random forests. Mach Learn 45(1):5–32CrossRefzbMATHGoogle Scholar
  5. Burnap P, Gibson R, Sloan L, Southern R, Williams M (2016) 140 Characters to victory? Using twitter to predict the UK 2015 general election. Electoral Stud 41:230–233CrossRefGoogle Scholar
  6. Ceron A, Curini L, Iacus SM, Porro G (2014) Every tweet counts? How sentiment analysis of social media can improve our knowledge of citizenspolitical preferences with an application to Italy and France. New Media Soc 16(2):340–358CrossRefGoogle Scholar
  7. Cesario E, Congedo C, Marozzo F, Riotta G, Spada A, Talia D, Trunfio P, Turri C (2015) Following soccer fans from geotagged tweets at fifa world cup 2014. In: Proceedings of the 2nd IEEE conference on spatial data mining and geographical knowledge services, pp 33–38. Fuzhou, China. ISBN 978-1-4799-7748-2Google Scholar
  8. Cesario E, Iannazzo AR, Marozzo F, Morello F, Riotta G, Spada A, Talia D, Trunfio P (2016) Analyzing social media data to discover mobility patterns at expo 2015: methodology and results. In: The 2016 international conference on high performance computing and simulation (HPCS 2016), pp. 230–237. Innsbruck, Austria. ISBN: 978-1-5090-2088-1.Google Scholar
  9. Dallmann A, Lemmerich F, Zoller D, Hotho A (2015) Media bias in German online newspapers. In: Proceedings of the 26th ACM conference on hypertext and social media, pp 133–137. ACMGoogle Scholar
  10. Elmer G (2013) Live research: Twittering an election debate. New Media Soc 15(1):18–30.  https://doi.org/10.1177/1461444812457328 CrossRefGoogle Scholar
  11. Franch F (2013) 2010 UK election prediction with social media. J Inform Technol Polit 10(1):57–71.  https://doi.org/10.1080/19331681.2012.705080 CrossRefGoogle Scholar
  12. Gokulakrishnan B, Priyanthan P, Ragavan T, Prasath N, Perera A (2012) Opinion mining and sentiment analysis on a twitter data stream. In: 2012 International conference on advances in ICT for emerging regions (ICTer), pp 182–188. IEEEGoogle Scholar
  13. Gonzalez-Bailon S, Banchs RE, Kaltenbrunner A (2010) Emotional reactions and the pulse of public opinion: measuring the impact of political events on the sentiment of online discussions. In: CoRR, abs/1009.4019Google Scholar
  14. Gruzd A, Roy J (2014) Investigating political polarization on twitter: a Canadian perspective. Policy Internet 6(1):28–45CrossRefGoogle Scholar
  15. Hanna R, Rohm A, Crittenden VL (2011) Were all connected: the power of the social media ecosystem. Bus Horiz 54(3):265–273CrossRefGoogle Scholar
  16. Hermida A, Fletcher F, Korell D, Logan D (2012) Share, like, recommend. J Stud 13(5–6):815–824.  https://doi.org/10.1080/1461670X.2012.664430 Google Scholar
  17. Hopkins DJ, King G (2010) A method of automated nonparametric content analysis for social science. Am J Polit Sci 54(1):229–247CrossRefGoogle Scholar
  18. Howard PN, Duffy A, Freelon D, Hussain MM, Mari W, Maziad M (2011) Opening closed regimes: what was the role of social media during the arab spring? SSRN.  https://doi.org/10.2139/ssrn.2595096
  19. Jungherr A (2016) Twitter use in election campaigns: a systematic literature review. J Inform Technol Polit 13(1):72–91.  https://doi.org/10.1080/19331681.2015.1132401 CrossRefGoogle Scholar
  20. Kagan V, Stevens A, Subrahmanian V (2015) Using twitter sentiment to forecast the 2013 Pakistani election and the 2014 Indian election. IEEE Intell Syst 30(1):2–5CrossRefGoogle Scholar
  21. Kwon S, Cha M, Jung K, Chen W, Wang Y (2013) Prominent features of rumor propagation in online social media. In: 2013 IEEE 13th international conference on data mining (ICDM), pp 1103–1108. IEEEGoogle Scholar
  22. Lerman K, Ghosh R (2010) Information contagion: an empirical study of the spread of news on digg and Twitter social networks. In: CoRR, abs/1003.2664Google Scholar
  23. Lievrouw L, Gillespie T, Boczkowski P, Foot K (2014) Materiality and media in communication and technology studies: an unfinished project. Media technologies: essays on communication, materiality, and society, pp 21–51Google Scholar
  24. Monti C, Rozza A, Zappella G, Zignani M, Arvidsson A, Colleoni E (2013) Modelling political disaffection from twitter data. In: Proceedings of the second international workshop on issues of sentiment discovery and opinion mining, p 3. ACMGoogle Scholar
  25. Murphy J, Link MW, Childs JH, Tesfaye CL, Dean E, Stern M, Pasek J, Cohen J, Callegaro M, Harwood P (2014) Social media in public opinion research executive summary of the aapor task force on emerging technologies in public opinion research. Public Opin Q 78(4):788.  https://doi.org/10.1093/poq/nfu053 CrossRefGoogle Scholar
  26. Nulty P, Theocharis Y, Popa SA, Parnet O, Benoit K (2016) Social media and political communication in the 2014 elections to the European parliament. Electoral Stud 44:429–444CrossRefGoogle Scholar
  27. O’Connor B, Balasubramanyan R, Routledge BR, Smith NA (2010) From tweets to polls: linking text sentiment to public opinion time series. ICWSM 11(122–129):1–2Google Scholar
  28. Pang B, Lee L (2008) Opinion mining and sentiment analysis. Found Trends Inform Retr 2(1–2):1–135.  https://doi.org/10.1561/1500000011 Google Scholar
  29. Talia D, Trunfio P, Marozzo F (2015) Data analysis in the cloud. Elsevier, AmsterdamGoogle Scholar
  30. Tufte ER (1986) The visual display of quantitative information. Graphics Press, CheshireGoogle Scholar
  31. Tumasjan A, Sprenger TO, Sandner PG, Welpe IM (2010) Predicting elections with Twitter: what 140 characters reveal about political sentiment. ICWSM 10(1):178–185Google Scholar
  32. Van Asch V (2013) Macro-and micro-averaged evaluation measures. Technical reportGoogle Scholar
  33. Wagner JP (2017) The media and national identity: local newspapers coverage of Scottish independence during the campaign of the 2014 Scottish independence referendum. In: Dealing with the localGoogle Scholar
  34. Zhang K, Cheng Y, Xie Y, Honbo D, Agrawal A, Palsetia D, Lee K, Liao WK, Choudhary A (2011) SES: sentiment elicitation system for social media data. In: 2011 IEEE 11th international conference on data mining workshops (ICDMW), pp 129–136. IEEEGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2017

Authors and Affiliations

  1. 1.DIMESUniversity of CalabriaRendeItaly
  2. 2.Information Sciences InstituteUniversity of Southern CaliforniaMarina del ReyUSA

Personalised recommendations