7.1 ANALÍSIS DE LOS CRITERIOS DE DISEÑO
7.2.2.2.8 Otros aportes de caudal
The exact correlation between disinformation and the political opinion and voting behaviour of individuals is not scientifically proven.579 US-related studies have shown that people have difficulties determining when a particular piece of news is false,580 and many of those who see false stories actually believe them.581 People are more likely to be affected by inaccurate information if they see more and more recent messages reporting facts, irrespective of whether they are true.582 There is also reason to believe that audio-visual messages can be both more persuasive and more easily spread than textual messages, but we do not know nearly enough about these dynamics – most research to date has focused on textual rather than visual and audio-visual misinformation.583 At the same time, people often provide multiple rationales for their opinions and do not strictly base them on facts.584 Therefore, even if they are exposed to true or false information, it does not necessarily mean that they are going to act on it.
Researchers are also using empirical methods to study the functioning and effectiveness of digital amplification mechanisms. Some of the studies in this field suggest that manipulation of people’s newsfeed or search results
576 Schmitt, Michael N.: Tallinn Manual 2.0. Cambridge University Press, 2017. Rule 26.
577 Network and Information Security (NIS) Directive (2016/1148); Joint Communication: Resilience, Deterrence and Defence: Building strong cybersecurity for the EU (JOIN(2017) 450 final).
578 See more at: Commission Recommendation (EU) 2017/1584. 13. Sept. 2017. on coordinated response to large-scale cybersecurity incidents and crises. https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/ ?uri=CELEX:32017H1584&from=EN
579 Roozenbeek, Jon and van der Linden, Sander, The Fake News Game: Actively Inoculating Against the Risk of Misinformation, From: https://www.cam.ac.uk/sites/www.cam.ac.uk/files/fakenews_latest_jrr_aaas.pdf , pp. 3-4: “Although extensive research exists on political misinformation (for a recent review, see Flynn, Nyhan, & Reifler, 2017), there is some debate about the extent to which fake news influences public opinion (Shao et al., 2017; van der Linden, 2017), including social media “echo chambers” and “filter bubbles” (Bakshy, Messing,
& Adamic, 2015; Flaxman, Goel, & Rao, 2016; Fletcher & Nielsen, 2017; Guess et al., 2018)”.
580 European Parliament, Fake news' and the EU's response (April 2017),
http://www.europarl.europa.eu/RegData/etudes/ATAG/2017/599384/EPRS_ATA%282017%29599384_EN.pdf
581 Allcott H. and Gentzkow M., Social Media and Fake News in the 2016 Election (Spring 2017). Stanford University, Journal of Economic Perspectives, Vol. 31, No. 2, pp. 211-236. https://web.stanford.edu/~gentzkow/research/fakenews.pdf, p. 212 582 Tucker, J. et al., Social media, political polarization and political disinformation: a review of the scientific literature. Hewlett Foundation, March 2018, pp. 40-48. https://hewlett.org/wp-content/uploads/2018/03/Social-Media-Political-Polarization- and-Political-Disinformation-Literature-Review.pdf
583 Ibid. 584 Ibid., p. 51.
could influence their voting behaviour: for example, when social platform users were told how their friends had said they had voted, this prompted a statistically significant increase in the segment of the population (0.14 % of the voting age population or about 340 000 voters) to vote in the congressional mid-term elections in 2010.585 In another study, researchers claimed that differences in Google Search results were capable of shifting the voting preferences of undecided voters by 20 %.586 In the commercial context, empirical research has shown how adapting messages to the psychological characteristics of individuals can directly influence their (purchase) behaviour.587 Other researchers challenged the conventional wisdom of the realities of political micro-targeting. The paper, published in August 2018, found evidence that political “messages [during the 2017 UK general election campaign] adhere closely to national campaign narratives” and “did not appear to be greatly more negative than other traditional modes of communication”.
Empirical studies about the effect of propaganda on public opinion are rare, but recent independent empirical (longitudinal) academic research studies have found that Hungarian governmental communication putting migration in a negative light resulted in a growth of xenophobia especially among people living in the countryside, the less educated, and the elderly,588 i.e. that part of the population whose informational environment was limited to government-friendly media because of the regional or social or educational circumstances.589 The correlation between lack of diversity (whether supply-side such as with an autocratic media system, or demand-side, such as with filter bubbles) and susceptibility to manipulation would be worthy of further research.590
Cause and effect relationships had also been very much contested in traditional media theory.591 The correlation between violent audiovisual content and the harm caused among children and youth, as well as the effect of content on the formation of political opinions has been examined repeatedly by experiments, and the results were often contradictory. This did not prevent legislators around the globe from restricting violent content and hate speech on mass media.
The regulation of mass media has been justified by three theoretical arguments: (1) The “pervasive effect”592 of audiovisual media. While the early internet was regarded as a ‘pull’ type medium demanding a more conscious
585; Allcott H. and Gentzkow M., Social Media and Fake News in the 2016 Election (Spring 2017), Stanford University, Journal of Economic Perspectives, Vol. 31, No. 2, pp. 211-236., p.219)
586 Zuiderveen Borgesius, F. & Trilling, D. & Möller, J. & Bodó, B. & de Vreese, C. & Helberger, N. (2016). Should we worry about filter bubbles?. Internet Policy Review, 5(1). DOI: 10.14763/2016.1.401, p. 9. Regarding search engine manipulation, also see: Epstein R and Robertson RE, ‘The Search Engine Manipulation Effect (SEME) and Its Possible Impact on the Outcomes of Elections.’ (2015) 112 Proceedings of the National Academy of Sciences of the United States of America E4512.
http://www.pnas.org/content/112/33/E4512.abstract?tab=author-info
587 Matz, S.C. et al., Psychological targeting as an effective approach to digital mass persuasion, PNAS November 28, 2017 114 (48) 12714-12719, https://www.pnas.org/content/114/48/12714
588 Kolozsi Ádám (2016): Sosem látott mértékű a magyarországi idegenellenesség, https://index.hu/tudomany/
2016/11/17/soha_nem_latott_merteku_az_idegenellenesseg_magyarorszagon/ (letöltés: 2018. XI. 1.).
589 Mérték Médiaelemző Műhely (2016–2018): Szúrópróba, http://mertek.eu/wp-content/uploads/
2018/07/Sz%C3%BAr%C3%B3pr%C3%B3ba-25.pdf (letöltés: 2018. XI. 4.).
590 See also the results that social media usage that involves participation in several networks reduces mass political polarization and echo chambers. Martens, Bertin, Luis Aguiar, Estrella Gomez-Herrera Frank Mueller-Langer (2018), “The digital transformation of news media and the rise of disinformation and fake news. An economic perspective”, JRC Digital
Economy Working Paper 2018-02. https://ec.europa.eu/jrc/
sites/jrcsh/files/jrc111529.pdf 27.
591 See the contesting theories of Harold Lasswell (bullet, 1927), Paul Lazarsfeld (two-step influence, 1948), Joseph Klapper (selective perception, 1949), George Gerbner (cultivation, 1969), McCombs and Shaw (agenda-setting, 1972), Herman and Chomsky (framing, 1988), Dayan and Katz (performative effect, 1992) - to name a few.
consumption attitude from users, as opposed to the ‘push’ type of television,593 web 2.0 design, streaming video and especially handheld devices have radically changed this. Content selection algorithms also aim at maximising user-engagement and making the service addictive.594 Today’s social media encounters can be addictive and intrusive. (2) Reaching masses of people, including children. While the information landscape today is scattered, the market of social media platforms is significantly more concentrated than that of traditional media, with Facebook having 2 234 million users in 2018.595 (3) Scarcity of resources. While the scarcity of material resources is not any longer a hindrance, the scarcity of attention is becoming a significant obstacle in access to a diversity of content.596
Further research is needed on the demographic characteristics of those people who are most susceptible to manipulation. According to a recent study, a significant generational divide can be observed: people over 65 share seven times more fake news than young users.597
The generational divide can also be observed in the rapidly changing trends: the young generation prefers messaging services such as Snapchat,598 and WhatsApp, and more picture-based platforms like Pinterest or Instagram, whereas Facebook’s popularity (used by their parents and grandparents) has been slowly sinking (although still very dominant). The popularity of private messaging platforms and apps carries the risk that harmful content becomes submerged and is less apparent to researchers and policy-makers.
Overall, the use of social media in social and political communication and the effects of exposure to information and disinformation on individual beliefs and behaviour is one of the key areas that needs to be addressed in future research.
593 Ashcroft v. American Civil Liberties Union, 535 U.S. 564 (2002) Lessig, Lawrence: What Things Regulate Speech: CDA 2.0 vs. Filtering. https://cyber.harvard.edu/works/lessig/what_things.pdf. See also: Two eras of the internet: pull and push. 21.12.2014. http://cdixon.org/2014/12/21/two-eras-of-the-internet-pull-and-push/
594 European Data Protection Supervisor (EDPS), Opinion on online manipulation and personal data, 3/2018, p. 13 ,
https://edps.europa.eu/sites/edp/files/publication/18-03-19_online_manipulation_en.pdf
595 Instagram at the 6th place had 1 billion users. 595 See numbers at: https://www.statista.com/statistics/272014/global-social-
networks-ranked-by-number-of-users/. See also: Social Media Use in 2018. http://www.pewinternet.org/2018/03/01/social- media-use-in-2018/
596 Helberger, N., Katharina Kleinen-von Königslöw and Rob van der Noll (2015), "Regulating the new information intermediaries as gatekeepers of information diversity", info, Vol. 17, No. 6, p.50-71, (https://doi.org/ 10.1108/info-05-2015-0034)
597 Andrew Guess, Jonathan Nagler and Joshua Tucker: Less than you think: Prevalence and predictors of fake news dissemination on Facebook. Sci Adv 5(1), eaau4586. DOI: 10.1126/sciadv.aau4586
598 Kantar Media: News in social media and messaging apps. Qualitative research report Prepared for the Reuters Institute for the Study of Journalism, University of Oxford with the support of the Google News Initiative. Sept. 2018.