Investigating Italian disinformation spreading on Twitter in the context of 2019 European elections


Autoři: Francesco Pierri aff001;  Alessandro Artoni aff001;  Stefano Ceri aff001
Působiště autorů: Dept. of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy aff001
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0227821

Souhrn

We investigate the presence (and the influence) of disinformation spreading on online social networks in Italy, in the 5-month period preceding the 2019 European Parliament elections. To this aim we collected a large-scale dataset of tweets associated to thousands of news articles published on Italian disinformation websites. In the observation period, a few outlets accounted for most of the deceptive information circulating on Twitter, which focused on controversial and polarizing topics of debate such as immigration, national safety and (Italian) nationalism. We found evidence of connections between Italian disinformation sources and different disinformation outlets across Europe, U.S. and Russia, featuring similar, even translated, articles in the period before the elections. Overall, the spread of disinformation on Twitter was confined in a limited community, strongly (and explicitly) related to the Italian conservative and far-right political environment, who had a limited impact on online discussions on the up-coming elections.

Klíčová slova:

Centrality – Elections – Europe – Facebook – Italian people – Network analysis – Social networks – Twitter


Zdroje

1. Pierri F, Ceri S. False news on social media: a data-driven survey. ACM SIGMOD Record Vol 48 Issue 2 (June). 2019;.

2. Allcott H, Gentzkow M. Social media and fake news in the 2016 election. Journal of Economic Perspectives. 2017;31(2):211–36. doi: 10.1257/jep.31.2.211

3. Lazer DMJ, Baum MA, Benkler Y, Berinsky AJ, Greenhill KM, Menczer F, et al. The science of fake news. Science. 2018;359(6380):1094–1096. doi: 10.1126/science.aao2998 29590025

4. Ferrara E. Disinformation and social bot operations in the run up to the 2017 French presidential election. First Monday. 2017;22(8). doi: 10.5210/fm.v22i8.8005

5. Bastos MT, Mercea D. The Brexit botnet and user-generated hyperpartisan news. Social Science Computer Review. 2019;37(1):38–54. doi: 10.1177/0894439317734157

6. Vosoughi S, Roy D, Aral S. The spread of true and false news online. Science. 2018;359(6380):1146–1151. doi: 10.1126/science.aap9559 29590045

7. Shao C, Ciampaglia GL, Varol O, Yang KC, Flammini A, Menczer F. The spread of low-credibility content by social bots. Nature communications. 2018;9(1):4787. doi: 10.1038/s41467-018-06930-7 30459415

8. Shao C, Hui PM, Wang L, Jiang X, Flammini A, Menczer F, et al. Anatomy of an online misinformation network. PLOS ONE. 2018;13(4):1–23. doi: 10.1371/journal.pone.0196087

9. Grinberg N, Joseph K, Friedland L, Swire-Thompson B, Lazer D. Fake news on Twitter during the 2016 U.S. presidential election. Science. 2019;363(6425):374–378. doi: 10.1126/science.aau2706 30679368

10. Bovet A, Makse HA. Influence of fake news in Twitter during the 2016 US presidential election. Nature Communications. 2019;10(1):7. doi: 10.1038/s41467-018-07761-2 30602729

11. Pierri F, Piccardi C, Ceri S. Topology comparison of Twitter diffusion networks reliably reveals disinformation news. arXiv. 2019;.

12. Henley J. How populism emerged as an electoral force in Europe. The Guardian. 2018;.

13. Dennison S, Zerka P. The 2019 European election: How anti-Europeans plan to wreck Europe and what can be done to stop it. European council on foreign relations. 2019;.

14. Howard PN, Bradshaw S, Kollanyi B, Bolsolver G. Junk News and Bots during the French Presidential Election: What Are French Voters Sharing Over Twitter In Round Two?;.

15. Stella M, Ferrara E, De Domenico M. Bots increase exposure to negative and inflammatory content in online social systems. Proceedings of the National Academy of Sciences. 2018;115(49):12435–12440. doi: 10.1073/pnas.1803470115

16. Hedman F, Sivnert F, Howard P. News and political information consumption in Sweden: Mapping the 2018 Swedish general election on Twitter; 2018.

17. Kollanyi B, Howard PN. Junk news and bots during the German parliamentary election: What are German voters sharing over Twitter; 2017.

18. Marchal N, Kollanyi B, Neudert LM, Howard PN. Junk News During the EU Parliamentary Elections: Lessons from a Seven-Language Study of Twitter and Facebook. 2019;.

19. Commission E. Tackling online disinformation; 2019. Available from: https://ec.europa.eu/digital-single-market/en/tackling-online-disinformation.

20. Nielsen RK, Newman N, Fletcher R, Kalogeropoulos A. Reuters Institute Digital News Report 2019. Report of the Reuters Institute for the Study of Journalism. 2019;.

21. Del Vicario M, Gaito S, Quattrociocchi W, Zignani M, Zollo F. News consumption during the Italian referendum: A cross-platform analysis on facebook and twitter. In: 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA). IEEE; 2017. p. 648–657.

22. Vicario MD, Quattrociocchi W, Scala A, Zollo F. Polarization and fake news: Early warning of Potential misinformation targets. ACM Transactions on the Web (TWEB). 2019;13(2):10.

23. Giglietto F, Iannelli L, Rossi L, Valeriani A, Righetti N, Carabini F, et al. Mapping Italian News Media Political Coverage in the Lead-Up to 2018 General Election. Available at SSRN: https://ssrncom/abstract=3179930. 2018;.

24. AGCOM. News vs Fake nel sistema dell’informazione. Report available at: https://wwwagcomit/documents/10179/12791486/Pubblicazione+23-11-2018/93869b4f-0a8d-4380-aad2-c10a0e426d83?version=10. 2018;.

25. Cantarella M, Fraccaroli N, Volpe R. Does Fake News Affect Voting Behaviour? Available at SSRN: https://ssrncom/abstract=3402913. 2019;.

26. Avaaz. Far Right Networks of Deception. Available at: https://avaazimagesavaazorg/Avaaz%20Report%20Network%20Deception%2020190522pdf. 2019;.

27. Shao C, Ciampaglia GL, Flammini A, Menczer F. Hoaxy: A Platform for Tracking Online Misinformation. In: Proceedings of the 25th International Conference Companion on World Wide Web. WWW’16 Companion. Republic and Canton of Geneva, Switzerland: International World Wide Web Conferences Steering Committee; 2016. p. 745–750. Available from: https://doi.org/10.1145/2872518.2890098.

28. Hui PM, Shao C, Flammini A, Menczer F, Ciampaglia GL. The Hoaxy misinformation and fact-checking diffusion network. In: Twelfth International AAAI Conference on Web and Social Media; 2018.

29. Zollo F, Bessi A, Del Vicario M, Scala A, Caldarelli G, Shekhtman L, et al. Debunking in a world of tribes. PloS one. 2017;12(7):e0181821. doi: 10.1371/journal.pone.0181821 28742163

30. Rieder B. Studying Facebook via data extraction: the Netvizz application. In: Proceedings of the 5th annual ACM web science conference. ACM; 2013. p. 346–355.

31. Hagberg A, Swart P, S Chult D. Exploring network structure, dynamics, and function using NetworkX. Los Alamos National Lab.(LANL), Los Alamos, NM (United States); 2008.

32. Barabási AL. Network science. Cambridge university press; 2016.

33. Batagelj V, Zaversnik M. An O(m) algorithm for cores decomposition of networks. arXiv preprint cs/0310049. 2003;.

34. Fortunato S, Hric D. Community detection in networks: A user guide. Physics reports. 2016;659:1–44. doi: 10.1016/j.physrep.2016.09.002

35. Blondel VD, Guillaume JL, Lambiotte R, Lefebvre E. Fast unfolding of communities in large networks. Journal of statistical mechanics: theory and experiment. 2008;2008(10):P10008. doi: 10.1088/1742-5468/2008/10/P10008

36. Girvan M, Newman ME. Community structure in social and biological networks. Proceedings of the national academy of sciences. 2002;99(12):7821–7826. doi: 10.1073/pnas.122653799

37. Freeman LC. A set of measures of centrality based on betweenness. Sociometry. 1977; p. 35–41. doi: 10.2307/3033543

38. Page L, Brin S, Motwani R, Winograd T. The PageRank citation ranking: Bringing order to the web. Stanford InfoLab; 1999.

39. Mann HB. Nonparametric tests against trend. Econometrica: Journal of the Econometric Society. 1945; p. 245–259. doi: 10.2307/1907187

40. Kendall MG. Rank correlation methods. Griffin. 1948;.

41. Efron B, Hastie T. Computer age statistical inference. vol. 5. Cambridge University Press; 2016.

42. Morstatter F, Pfeffer J, Liu H, Carley KM. Is the sample good enough? comparing data from twitter’s streaming api with twitter’s firehose. In: Seventh international AAAI conference on weblogs and social media; 2013.

43. Ratkiewicz J, Conover MD, Meiss M, Gonçalves B, Flammini A, Menczer FM. Detecting and tracking political abuse in social media. In: Fifth international AAAI conference on weblogs and social media; 2011.

44. McCombs ME, Shaw DL, Weaver DH. New directions in agenda-setting theory and research. Mass communication and society. 2014;17(6):781–802. doi: 10.1080/15205436.2014.964871

45. Vargo CJ, Guo L, Amazeen MA. The agenda-setting power of fake news: A big data analysis of the online media landscape from 2014 to 2016. New Media & Society. 2018;20(5):2028–2049. doi: 10.1177/1461444817712086

46. Horne BD, Adali S. This just in: fake news packs a lot in title, uses simpler, repetitive content in text body, more similar to satire than real news. arXiv preprint arXiv:170309398. 2017;.

47. Zajonc RB. Mere exposure: A gateway to the subliminal. Current directions in psychological science. 2001;10(6):224–228. doi: 10.1111/1467-8721.00154

48. Blei DM, Ng AY, Jordan MI. Latent dirichlet allocation. Journal of machine Learning research. 2003;3(Jan):993–1022.

49. Vargo CJ, Guo L, McCombs M, Shaw DL. Network issue agendas on Twitter during the 2012 US presidential election. Journal of Communication. 2014;64(2):296–316. doi: 10.1111/jcom.12089

50. Wang P, Angarita R, Renna I. Is this the era of misinformation yet: combining social bots and fake news to deceive the masses. In: Companion Proceedings of the The Web Conference 2018. International World Wide Web Conferences Steering Committee; 2018. p. 1557–1561.

51. International A. Il Barometro dell’odio—Elezioni europee 2019. Available at: https://wwwamnestyit/cosa-facciamo/elezioni-europee/. 2019;.

52. Conti N. Elezioni europee, ma poca Europa. La Repubblica. 2019;.

53. FactCheckEU. Good news and bad news after election week-end. 2019;.

54. McCombs M. Setting the agenda: Mass media and public opinion. John Wiley & Sons; 2018.

55. Davis CA, Varol O, Ferrara E, Flammini A, Menczer F. Botornot: A system to evaluate social bots. In: Proceedings of the 25th International Conference Companion on World Wide Web. International World Wide Web Conferences Steering Committee; 2016. p. 273–274.

56. Maslov S, Sneppen K. Specificity and stability in topology of protein networks. Science. 2002;296(5569):910–913. doi: 10.1126/science.1065103 11988575


Článek vyšel v časopise

PLOS One


2020 Číslo 1