Fake News Consumption: History
View Latest Version
Please note this is an old version of this entry, which may differ significantly from the current revision.
Subjects: Others
Contributor:
João Pedro Baptista

This entry analyzes some of the psychological, partisan and ideological factors that influence the consumption of fake news. For a better understanding of the consumption of fake news, consult the review paper of the authors [1].

  • media consumption
  • fake news
  • social media
  • political ideology

1.Introduction [1]

This review seeks to be an addition to the literature, and its main objective is to analyze the phenomenon of fake news from the perspective of the consumer and to understand the characteristics of fake news articles that motivate their viral spread and which factors are associated with the selection and consumption of fake news in an online environment, in the search to define a profile for the true consumer of online disinformation.
This review focuses on consumer motivations (user/reader) and the structure/presentation of fake news to ascertain the apparent success and proliferation of this type of online disinformation. The factors associated with the dynamics of social media (recommendation algorithms, echo chambers, filter bubbles, malicious social bots) that also contribute a lot to the spread of fake news, were not addressed. With this review, we intend to understand the phenomenon of isolated fake news, in an independent approach to the characteristics of the digital universe to which it belongs. Our goals are to identify the main factors that influence fake news’ belief and sharing and to identify differences and similarities between fake news and real news, in order to highlight the relevance of these characteristics for their dissemination. We know that some stories are more likely to go viral than others; that some headlines are more attractive, and that users tend to select information based on their party and ideological identity and on their social and psychological characteristics.

2. The Role of the Structure of Fake News

The way in which the structure (for example, from the images chosen, the format of the titles and the language used in the text) of fake news is presented can help explain the reasons for it becoming viral on social media. This analysis intends to focus only on these aspects of fake news, that is, on its formats, content and standards used. Heath (1996) showed that people have a preference for exaggeration, especially if the news is exaggeratedly bad, so (fake) news that presents accidents, disasters or crimes can generate greater emotional sharing [2][3]. Still, fake political news spreads quickly, like that regarding terrorism, natural disasters, urban legends or financial information [4]. Vosoughi et al. (2018) demonstrate that false content about politics was not only more widely disseminated, but also reached a larger number of people, compared to other subjects. Without specifying the category of false information, these authors showed that falsehood spreads faster than truthful content, stimulating different feelings in those who read it: disgust, fear or surprise[4]. On the other hand, Humprecht(2019) demonstrated that, unlike the USA and the United Kingdom (where online disinformation is mostly political and partisan), in Germany and Austria, sensationalist stories predominate over political content [5]. In an analysis of the fact-checkers in these four countries, the author found that online disinformation in English-speaking countries tends to target political actors, whereas in German-speaking countries, the main focus is immigrants, holding them responsible for current political, economic or social situations. For example, in Brazil and Portugal, one of the main targets of online disinformation is also corruption and politics [6][7] . Budak (2019) found that the topics covered during the American elections on Twitter by the traditional media are different compared to fake news agencies. Traditional news focused more on policies related to the economy, elections, women or the environment[8]. Budak (2019) shows that the coverage of candidates (Hillary and Trump) from the fake news agency is different from the media. The most frequent words used in detected fake news, such as “sex”, ”death”, ”corrupt”, ”illegal”, ”alien” or ”lie”, they refer to sensational or outrageous content, unlike traditional media[8].

The literature has demonstrated, in fact, that the lexicon used by fake news is more informal and simple in detail and in technical production, not only in the title of the piece, but also throughout the text [9]. Several elements taken into account by the producers of fake news, such as simple and impressive messages, with attractive headlines that appeal to the feelings of the public, through clickbaiting, are essential for repeated disclosure[10]. These factors make the story not only more attractive, but also more persuasive [11].In a content analysis, Horne and Adali (2017) found that fake news articles can be distinguished from real news by their lexical coherence. “Real news articles are significantly longer than fake news articles and fake news articles use fewer technical words, smaller words, less punctuation, fewer quotes, and more lexical redundancy”[9]. The authors report that fake news needs lower levels of education to be interpreted.These characteristics allow us to verify that fake news also plays a persuasive role through mostly heuristic methods. In other words, fake news requires less effort and attention[9][12]. The association of ideas and the reader’s interpretations may be less logical and based only on their titles, since fake titles have significantly more words, have too much content and exaggeration (through hyperbolic words) that resemble clickbait [9][13]. Wiggins (2017) considers that the sensationalist and attractive way in which most fake news is presented fits into the peripheral route of persuasion, which “implies focusing on those elements not central to the argument or message, but paying more attention to how the message is presented”[11], as opposed to the central route.

3. Who are Fake News consumers?

The belief, consumption and dissemination of fake news may be related to several aspects: for example, the growing distrust in the media[14][15] , the users’ level of education [16][17], age and gender [18][19][20], party affiliation and ideological identity[21][22][23], with the availability and time dedicated to social media[24] or with our cognitive ability [25][26].

Too much time spent on social media increases the user’s exposure to false or illegitimate content, especially if the user has a very active political identity or participation [27]. The exposure can also become repeated, making the content more familiar and easily accessible, which can induce a belief [28]. Even though this exposure is later denied by fact-checkers, the user can continue to believe in its content [29](Pennycook et al. 2018).
Despite this, Halpern et al. (2019) concluded that the use of social media is not related to the belief in fake news. The authors argue that more connected users may have greater knowledge in selecting quality information, exposing themselves less to this type of disinformation [27]. It should be noted that some studies have found that the fake news audience is smaller than the real news audience [21][30].Regarding the American election period, in 2016, Guess et al. (2019) even mention that some warnings about the echo chambers had been exaggerated, since they estimated that only one in four Americans visited disinformation websites during the elections [30]. In addition, the audience that consumes fake news is not only limited to filter bubbles and echo chambers, since this audience is also exposed, on social media, to real news [24].
In Italy and France, in 2017, most fake news sites reached less than 1% of the online population per month, even though the engagement generated by some fake news on Facebook has exceeded the engagement generated by the most popular real news.
However, this was not the case in most situations [31]. Fake news has a smaller audience than mainstream media, and the levels of distrust in these traditional media sources are lower. Still, online disinformation is currently a political weapon and Facebook is one of the main means of spreading fake news [32][33], while it remains the preferred social network for accessing news. What justifies these results?

The consumption of fake news may be related to the user’s availability to use social media. Nelson and Taneja (2018) demonstrated that the selection of information and TV programming has to do with the time available and our schedules, and not exactly with the preferences of the public[24]. Users with more time available for the internet not only tend to look for other alternative means[34] , but are more exposed to all types of information, especially the most popular ones. The time spent on Facebook and Google is positively correlated with the consumption of fake news[24]. Additionally, the user’s level of education can influence the belief in and dissemination of fake news. More educated people, especially young people, are less likely to share false information[16] . Flynn et al. (2017) found that the level of education can be a tool in combating the spread of disinformation online[17]. Nevertheless, Manalu et al. (2018) found that users aged between 15 and 30 years are more susceptible to believe in fake news, because they are more exposed.
The Digital News Report 2019 points out that young people are not so predisposed to “to work hard for their news”, and prefer “easy” and “fun” access [33]. Some studies [35][36]have already shown that school and college students have a hard time distinguishing between false and true information. Contrary, in a study that sought to analyze the profiles of users who believed in fake news, it was shown that it is older people and those who are more outgoing and friendly who trust fake news[18].
Munger et al. (2018) concluded that the elderly have a greater preference for clickbait headlines, that is, titles that are designed with the objective of attracting the attention of the reader to click on content of “doubtful value or interest” [10]. Consumption can also vary due to gender differences: women are more likely to share false information, although it is men who prefer to consume news through social media [18].
These demographic variables can also be related to the belief and spread of false rumors. Lai et al. (2020) found that women are more likely to believe rumors. The same is true of less literate or educated individuals[37] . However, the traits related to the personality of each person can also be related to the belief in false rumors, such as people with high values of neuroticism and extroversion[38][37].
From a psychological perspective, several studies[39][40][25][26] found that analytical and intuitive thoughts can interfere with the evaluation of false or true information. According to Pennycook and Rand (2017), the most intuitive individuals are more spontaneous, perform quickly with little attention or intellectual reflection, which turns them more likely to believe in “bullshit” , since the majority of the public is limited to reading the headlines [41]. 
Related to this aspect, [25][42][39] point out, for example, that liberals tend to be more analytical than conservatives. Conservatives rely more on intuition, so conservatives may be more likely to consume fake news or to believe in “bullshit”. Jost et al. (2003) analyzed the social behavior associated with conservatism and found that ideologically right-wing people, in the social sense, have a greater tendency to reject complex topics and are more dependent on implicit reasoning[43].
Tetlock (1983) had previously found that conservatism is associated with a more closed mind, which offers resistance to complexity and change, drawing lessons from the world around it through quick judgments, sometimes based on stereotypes [44].
The belief in fake news can be greater in people prone to delusion, with psychotic thoughts or who follow unusual opinions or ideas such as being aware of conspiracy theories or paranormal phenomena [45].

The entry is from 10.3390/socsci9100185

 

References

  1. João Pedro Baptista; Anabela Gradim; Understanding Fake News Consumption: A Review. Social Sciences 2020, 9, 185, 10.3390/socsci9100185.
  2. Jonathan Bright; The Social News Gap: How News Reading and News Sharing Diverge. Journal of Communication 2016, 66, 343-365, 10.1111/jcom.12232.
  3. Chip Heath; Do People Prefer to Pass Along Good or Bad News? Valence and Relevance of News as Predictors of Transmission Propensity. Organizational Behavior and Human Decision Processes 1996, 68, 79-94, 10.1006/obhd.1996.0091.
  4. Soroush Vosoughi; Deb Roy; Sinan Aral; The spread of true and false news online. Science 2018, 359, 1146-1151, 10.1126/science.aap9559.
  5. Edda Humprecht; Where ‘fake news’ flourishes: a comparison across four Western democracies. Information, Communication & Society 2018, 22, 1973-1988, 10.1080/1369118x.2018.1474241.
  6. Cardoso, Gustavo, Inês Narciso, José Moreno, and Nuno Palma. 2019. Report—Online Disinformation duringPortugal’s 2019 Elections. Lisbon: MEDIALAB & Democracy Reporting International.
  7. ISCTE. 2019. Disinformation Risks in Portugal’s Election More Brazil than Europe? Risk Assessment: Online Manipulation Ahead of the Portuguese Parliamentary Elections. Available online: https://medialab.iscte-iul. pt/desinformacao-risco-de-interferencia-nas-eleicoes-e-reduzido-2/ (accessed on 15 October 2020).
  8. Ceren Budak; What happened? The Spread of Fake News Publisher Content During the 2016 U.S. Presidential Election. The World Wide Web Conference on - WWW '19 2019, ., 139-150, 10.1145/3308558.3313721.
  9. Benjamin D. Horne; Sibel Adali; This Just In: Fake News Packs a Lot in Title, Uses Simpler, Repetitive Content in Text Body, More Similar to Satire than Real News. In Proceedings of the Eleventh International AAAI Conference on Web and Social Media 2017, null, null, .
  10. Munger, Kevin, Mario Luca, Jonathan Nagler, and Joshua Tucker. 2018. The Effect of Clickbait. Available online: https://www.semanticscholar.org/paper/The-Effect-of-Clickbait-*-Munger-Luca/9edda403530e9a45dd0b756ea0b938797dce6a82 (accessed on 15 October 2020).
  11. Bradley E. Wiggins; Navigating an Immersive Narratology. International Journal of E-Politics 2017, 8, 16-29, 10.4018/ijep.2017070102.
  12. Baptista, João; Ethos, pathos e logos. Análise comparativa do processo persuasivo das (fake) news. Eikon 2020, 1, 43-54, .
  13. A Bazaco; M Redondo; P Sánchez-García; Clickbait as a strategy of viral journalism: conceptualisation and methods. Clickbait as a strategy of viral journalism: conceptualisation and methods 2019, 74, 94-115, 10.4185/rlcs-2019-1323en.
  14. Americans’ trust in mass media sinks to new low. . Gallup News. Retrieved 2020-11-4
  15. Nielsen, Rasmus Kleis, and Lucas Graves. 2017. ‘News You Don’t Believe’: Audience Perspectives on Fake News. Oxford: Reuters Institute for the Study of Journalism, Available online: https://ora.ox.ac.uk/objects/uuid:6eff4d14-bc72-404d-b78a-4c2573459ab8 (accessed on 15 October 2020).
  16. Mihai-Ionuț Pop; Irina Ene; Influence of the educational level on the spreading of Fake News regarding the energy field in the online environment. Proceedings of the International Conference on Business Excellence 2019, 13, 1108-1117, 10.2478/picbe-2019-0097.
  17. D.J. Flynn; Brendan Nyhan; Jason Reifler; The Nature and Origins of Misperceptions: Understanding False and Unsupported Beliefs About Politics. Political Psychology 2017, 38, 127-150, 10.1111/pops.12394.
  18. Kai Shu; Suhang Wang; Huan Liu; Understanding User Profiles on Social Media for Fake News Detection. 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR) 2018, ., 430-435, 10.1109/mipr.2018.00092.
  19. Tant, ău, Adrian, Mihai Pop, and Alexandra Cătălina Chinie. 2019. Quantitative Analysis Regarding the Probabilityof Spreading Fake News Based on Age. New Trends in Sustainable Business and Consumption, 649. Available online: https://www.researchgate.net/profile/Ann_Katrin_Arp/publication/333902657_Study_ on_European_funding_programmes_for_sustainable_development/links/5dbaf94d299bf1a47b05a8d3/ Study-on-European-funding-programmes-for-sustainable-development.pdf#page=649 (accessed on 15 October 2020).
  20. Rouli Manalu; Tandiyo Pradekso; Djoko Setyabudi; Understanding the Tendency of Media Users to Consume Fake News. Jurnal ILMU KOMUNIKASI 2018, 15, 1-16, 10.24002/jik.v15i1.1322.
  21. Hunt Allcott; Matthew Gentzkow; Social Media and Fake News in the 2016 Election. Journal of Economic Perspectives 2017, 31, 211-236, 10.1257/jep.31.2.211.
  22. Joseph E. Uscinski; Casey Klofstad; Matthew D. Atkinson; What Drives Conspiratorial Beliefs? The Role of Informational Cues and Predispositions. Political Research Quarterly 2016, 69, 57-71, 10.1177/1065912915621621.
  23. Regina Rini; Fake News and Partisan Epistemology. Kennedy Institute of Ethics Journal 2017, 27, E-43-43, 10.1353/ken.2017.0025.
  24. Jacob L Nelson; Harsh Taneja; The small, disloyal fake news audience: The role of audience availability in fake news consumption. New Media & Society 2018, 20, 3720-3737, 10.1177/1461444818758715.
  25. Gordon Pennycook; David G. Rand; Who Falls for Fake News? The Roles of Analytic Thinking, Motivated Reasoning, Political Ideology, and Bullshit Receptivity. SSRN Electronic Journal 2017, null, ., 10.2139/ssrn.3023545.
  26. David G. Rand; David G. Rand; Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. Cognition 2019, 188, 39-50, 10.1016/j.cognition.2018.06.011.
  27. Daniel Halpern; Sebastián Valenzuela; James Katz; Juan Pablo Miranda; From Belief in Conspiracy Theories to Trust in Others: Which Factors Influence Exposure, Believing and Sharing Fake News. Lecture Notes in Computer Science 2019, ., 217-232, 10.1007/978-3-030-21902-4_16.
  28. Anna Elisabetta Galeotti; Believing fake news. Post-Truth, Philosophy and Law 2019, ., 58-76, 10.4324/9780429450778-6.
  29. Gordon Pennycook; Tyrone D. Cannon; David G. Rand; Prior exposure increases perceived accuracy of fake news.. Journal of Experimental Psychology: General 2018, 147, 1865-1880, 10.1037/xge0000465.
  30. Andrew Guess; Jonathan Nagler; Joshua Tucker; Less than you think: Prevalence and predictors of fake news dissemination on Facebook. Science Advances 2019, 5, eaau4586, 10.1126/sciadv.aau4586.
  31. Fletcher, Richard, Alessio Cornia, Lucas Graves, and Rasmus Kleis Nielsen. 2018. Measuring the Reach of ‘FakeNews’ and Online Disinformation in Europe. Reuters Institute Factsheet. Available online: http://www. digitalnewsreport.org/publications/2018/measuring-reach-fake-news-online-disinformation-europe/ (accessed on 15 October 2020).
  32. Bernal, Paul; Why Facebook Makes the Fake News Problem Inevitable.. Northern Ireland Legal Quarterly 2018, 69, 513-30, .
  33. Newman, Nic, Richard Fletcher, Antonis Kalogeropoulos, and Rasmus Nielsen. 2019. Reuters Institute DigitalNews Report 2019. Oxford: Reuters Institute for the Study of Journalism, vol. 2019.
  34. Elberse, Anita. 2008. Should You Invest in the Long Tail? Harvard Business Review 86: 88.
  35. Sarah McGrew; Joel Breakstone; Teresa Ortega; Mark Smith; Sam Wineburg; Can Students Evaluate Online Sources? Learning From Assessments of Civic Online Reasoning. Theory & Research in Social Education 2018, 46, 165-193, 10.1080/00933104.2017.1416320.
  36. Wineburg, Sam, Sarah McGrew, Joel Breakstone, and Teresa Ortega. 2016. Evaluating Information: The Cornerstone of Civic Online Reasoning. Stanford Digital Repository 8: 2018.
  37. Kaisheng Lai; Xiling Xiong; Xiaoya Jiang; Meiqi Sun; Lingnan He; Who falls for rumor? Influence of personality traits on false rumor belief. Personality and Individual Differences 2020, 152, 109520, 10.1016/j.paid.2019.109520.
  38. Bordia, Prashant, and Nicholas DiFonzo. 2017. Psychological Motivations in Rumor Spread. In Rumor Mills. Edited by Gary Alan Fine, Véronique Campion-Vicent and Chip Health. Abingdon-on-Thames: Routledge, pp. 87–102.
  39. Deppe, Kristen D., Frank J. Gonzalez, Jayme L. Neiman, Carly Jacobs, Jackson Pahlke, Kevin B. Smith, and John R. Hibbing.; Reflective Liberals and Intuitive Conservatives: A Look at the Cognitive Reflection Test and Ideology. . Judgment and Decision Making 2015, 10, 314-31, .
  40. Dan M. Kahan; Ideology, Motivated Reasoning, and Cognitive Reflection: An Experimental Study. SSRN Electronic Journal 2012, ., ., 10.2139/ssrn.2182588.
  41. Maksym Gabielkov; Arthi Ramachandran; Augustin Chaintreau; Arnaud Legout; Social Clicks. Proceedings of the 2016 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Science - SIGMETRICS '16 2016, ., 179-192, 10.1145/2896377.2901462.
  42. Briony Swire-Thompson; Adam J. Berinsky; Stephan Lewandowsky; Ullrich K. H. Ecker; Processing political misinformation: comprehending the Trump phenomenon. Royal Society Open Science 2017, 4, 160802, 10.1098/rsos.160802.
  43. John T. Jost; Jack Glaser; Arie W. Kruglanski; Frank J. Sulloway; Political conservatism as motivated social cognition.. Psychological Bulletin 2003, 129, 339-375, 10.1037/0033-2909.129.3.339.
  44. Philip E. Tetlock; Cognitive style and political ideology.. Journal of Personality and Social Psychology 1983, 45, 118-126, 10.1037//0022-3514.45.1.118.
  45. Karen M. Douglas; Joseph E. Uscinski; Robbie M. Sutton; Aleksandra Cichocka; Turkay Nefes; Chee Siang Ang; Farzin Deravi; Understanding Conspiracy Theories. Political Psychology 2019, 40, 3-35, 10.1111/pops.12568.
  46. Karen M. Douglas; Joseph E. Uscinski; Robbie M. Sutton; Aleksandra Cichocka; Turkay Nefes; Chee Siang Ang; Farzin Deravi; Understanding Conspiracy Theories. Political Psychology 2019, 40, 3-35, 10.1111/pops.12568.
More
©Text is available under the terms and conditions of the Creative Commons-Attribution ShareAlike (CC BY-SA) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
This entry is offline, you can click here to edit this entry!
ScholarVision Creations
Feedback