Reuters Institute Digital News Report (2019) confirms that the concern for distinguishing between ‘fake’ and ‘real’ news is still a topic relevant topic globally. The report shows that Brazil, South Africa, UK, Mexico and the US are some the countries most worried about ‘fake news’. The UK has the last year had the biggest increase in worrying about the credibility of news content (Reuters Institute, 2019:21).
This blog post will investigate the concept of ‘fake news’ and its implications on national and international politics. Firstly, it will present a definition of ‘fake news’. Second, it will present the two perspectives of ‘fake news’’ distribution and functions; economic and ideology. In this section I will present research on the usage of bots on Twitter, news consumption via WhatsApp, and theories on perceptions of news content. Finally, I present possible solutions to combat ‘fake news’, followed by a conclusion.
‘Fake news’, genres and subcategories
The many terms being used to describe the current worry of being misled by news in the populations of many countries (Reuters Institute, 2019) might be a reason why scholars, politicians and companies are struggling with restraining it. Tandoc et al. (2018) discusses this difficulty in an analysis of the term ‘fake news’ in 34 academic articles between 2003 and 2017. Here, ‘fake news’ is divided into different subcategories; satire, parody, fabricated, photo manipulation, advertisement, and propaganda. The subcategories are then divided again based on a model that considers the creators’ intent to deceive consumers and levels of facticity (Tandoc et al., 2018:147—148).
Babaei et al. (2019) divides ‘fake news’ into two subcategories; misinformation and disinformation. Misinformation referes to information that is simply wrong, as in rumours. While disinformation describes information that is intentionally wrong, is meant to mislead and not verifiable. Allcott and Gentzkow (2017:214) notes that some of the subcategories presented in Tandoc et al. (2018), as well as other types of news content, are not subcategories of fake news, but rather close genres; unintentional reporting mistakes, rumours, conspiracy theories, satire, false statements, and slander.
As this post is not on the definition of ‘fake news’, rather it is on ‘fake news’’ functions and implications, the definition used in this text will be based on the model of Tandoc et al. (2018) as well as the works of Alcott and Gentzkow (2017) and Babaei et al. (2019). ‘Fake news’ in this text will be refering to ‘intentonally and verifiable false content that deliberately present itself as verifiable true news content’. The theme of fake news focused on in this post will mostly be political. The reason for this definition is it takes into account that news articles with misinformation is not fake news and will be corrected when found out about, if not then it becomes intentional misinformation, therefore it becomes fake news. It also takes into account that satire, parody and advertisement often does not fully present itself as verifiable true news content, but that some types of propaganda, fabrication, photo manipulation and disinformation often will portray itself as true news content.
Why is fake news a problem?
To further investigate the implications of fake news, as defined above, it is beneficial to understand why the concept has generated this amount of attention and concern. Normative theories on the media, specifically news media, links itself to freedom of speech, freedom of information and the public sphere (Gripsrud, 2007; Oltedal, 2008; Sejersted, 2008). In this view of news media, the media becomes an extension of the modern democracy as their ‘watchdog’. The role of the watchdog is to watch over those in power (government, politicians, policy makers, employers and so on), make sure they do not abuse these powers, and to inform citizens of their actions and provide knowledge meant to form the public into ‘informed citizens’ (Skogerbø, 2008). Within the notion of Habermas’ concept of the public sphere the media, now very much online, has become a place for citizens to voice their opinion and have a public debate (Gripsrud, 2007; Van Aelst, 2017). News media’s task then, in the roles as democracy’s watchdog and public sphere, becomes not only to distribute these public opinions, but to distribute high quality and neutral information for the public to base their own opinions on (Skogerbø, 2008:45—48).
The rise of fake news can therefore become a threat to the normative expectations of what news media are supposed to offer the public. If citizens consume fake news and believe the content, their political actions might be shaped by the fake information they are given. Furthermore, if citizens are concerned about the spread of fake news, it might lead to declining trust levels in actual high quality and neutral information given to them.
Creation and distribution: the economics of fake news
As well as the democratic perspective of the media, the media must also be viewed in an economic perspective. Media companies are often dependent on economic profits to stay afloat on the media market. Although it might seem like a combination of the two perspectives would be the most beneficial as to keep the media as democracy’s watchdog as well as staying afloat, within this perspective, the role as democracy’s watchdog takes a backseat. Producing content which generates monetary growth becomes the main objective (Skogerbø, 2012). This then means that news media will have to produce news content that will generate clicks and engagement. Such content might not qualify as high quality, neutral and valuable information for the public to base their own opinions on.
According to research by Allcott and Gentzkow (2017:222—223), social media is one of several explanations for fake news’ growth. Close to 42 percent of fake news websites’ visitors come from social media referrals, as opposed to 10 percent for top news sites where almost half of their visitors come from direct browsing. The combination of fake news websites being easily created at a low price and the possibility to monetize the content is presented as another explanation, but visitors must then know the URLs to visit these sites. It is therefore more beneficial to spread single articles on social media sites with low, or non-existing, regulations on news content to generate visitors. The creators of fake news can therefore be located in one country but spread fake news content for another country (Allcott and Gentzkow, 2017). This has created concern about different countries’ involvement in other countries’ political elections (Vox, 2018).
Twitter has been called out as a space containing fake news, particularly when it comes to its spread by ‘bots’. ‘Bots’, in this post, refers to the definition provided by Murthy et al. (2016:4955) ‘Bots, at their simplest, are social media accounts that are controlled either wholly or in part by software agents’. On Twitter, bots can be portrayed as ‘regular users’ and share content which includes fake news. The concern about bots spreading fake news on Twitter and its effect on the political opinions of the public has become a topic in the press (BBC, 2017; Vox, 2018). However, studies indicate that bots might not have such a huge impact after all. One study found that fake news on Twitter spread considerable faster and wider than true news via peer-to-peer ‘retweeting’. The study investigated the spread with and without bots and concluded that fake news still spread faster and wider when bots were ruled out (Vosoughi et al., 2018). Another look into the usage of bots on Twitter attempted to recreate bots and bot networks (Murthy et al., 2016). However, because the study’s bots were low in followers and new, and therefore lacked the social capital, they did not manage spread its content effectively.
According to Reuters Institute (2019) mobile instant messaging services (MIMs) have had a noticeable increase in terms of usage and sharing news. WhatsApp is one of the MIMs that has shown itself to be heavily used for news in countries like Brazil (53%), Malaysia (50%), South Africa (48%) and Chile (40%) (Reuters Institute, 2019:38). The topic of using WhatsApp, mostly in the form of groups, as a source for news is still relatively new, but some research has been conducted on the phenomenon (Resende et al., 2019; Valenzuela et al., 2019). In the cases of both Brazil and Chile, WhatsApp groups were used to share political news, both fake and real, during the countries’ election campaigns. In the case of Brazil, Resende et al. (2019) presented a textual analysis of the attributes of misinformation being shared on WhatsApp. Messages with misinformation included more URLs, concentrated on fewer topics (presidential candidates and government projects) and were shared more frequently by more users than messages not including misinformation. For Chile, the results based on a two-wave panel survey showed that the usage of WhatsApp for news consumption had a positive correlation with political knowledge. The study also could not confirm that the usage of WhatsApp for news increased political ‘polarisation’ (Valenzuela et al., 2019). However, the increase of political ‘polarisation’ has been presented to be another explanation for the spread of fake news (Allcott and Gentzkow, 2017).
The results generated in the case of the spread of fake news on Twitter and WhatsApp implies that the spread of fake news is a sociotechnical phenomenon. For fake news to function it needs humans (social) to utilize social media og MIMs (technology) for mobility, therefore it becomes a sociotechnical process. This leads this post to another side of the rise of fake news, which is the ideological aspect.
When trust declines: the ideology of fake news
‘Polarisation’ entails having beliefs and attitudes that are on opposite sides of a spectrum. On the political spectrum it can be described as people who are more inclined to adhere to one or the other side of the political/ideological spectre, right-winged or left-winged (Hanitzsch et al., 2018:8). Countries like the US have seen massive polarisation when it comes to trust in the media. Despite generalised trust levels at 32 percentage both in 2018 and 2019, it does not mean the underlying statistics have gone unchanged. The rise of trust in the media on the political left side has increased from 49 to 53 percent, while the political right side has had trust levels go from 17 to 9 percent (Reuters Institute, 2019:21). This leads on to the concept of ‘hostile media phenomenon’. The ‘hostile media phenomenon’ (Vallone et al., 1985) describes how consumers believe neutral news articles sympathise with the opposite political ideology of the consumers themselves. If consumers do perceive neutral news as such, it is then believed that they will perform what is described as ‘selective exposure’ and ‘selective trust’. According to extensive research, ‘selective exposure’ involves consumers actively seeking out content that better correlates to their own personal ideological positions (Knudsen et al., 2018; Gil de Zúñiga et al., 2012; Marquart et al., 2016). These are not just American tendencies. Knudsen et al., (2018) analysed norwegian attitudes towards historically political newspapers based on readers own political ideology. The results reveal that readers are more inclined to trust newspapers that align with their own ideologies.
In other words, consumers who believe neutral news articles demonstrates politically and ideologically biased content will then seek out other biased content which supports their own biased ideological and political beliefs. Within this selected exposure, the consumers will likely display higher levels of trust towards the content that support their beliefs, which is described as ‘selective trust’ (Babaei et al., 2019; Knudsen et al., 2018). In the discussion of news media one can then fit the concepts of hostile media phenomenon, selective exposure and trust, and polarisation as a confirming circle. One cannot assume that the public will blatantly accept all information given by the media. This assumption becomes close to the ‘injection-model’, where consumers will uncritically accept the media’s message (Gripsrud, 2007:52). Tsfati og Cappella (2003), in their investigation of attitudes towards media and patterns in media consumption, assumes that consumers are rational and will seek out content they trust. Their study concluded that those sceptical towards mainstream news in actuality had a more diverse news media diet. However, this did not mean that the consumers trusted what they were exposed to but had higher trust in what aligned with their own beliefs. Still, the study admitted to not being able to enlighten if media sceptics seek out alternative media because they were sceptics, or if the increase of alternative media made them more sceptic towards mainstream media (Tsfati og Cappella, 2003:521). Another direction fake news can lead to is news avoidance. In the UK, the perceived polarised coverage of Brexit has increased news avoidance by 11 percent. As the reasons to avoid news content, not being able to rely on it being true was the third highest reason, with 34 percent (Reuters Institute, 2019:25).
In short, someone who already have politically polarised beliefs might also exhibit notions of hostile media phenomenon and therefore seek out, and have higher levels of trust in, biased news that aligns with their own political ideology, which can create higher levels of polarisation. This links into the sociotechnical way of viewing the functions of fake news. For fake news to function it requires consumers to already exhibit underlying factors that makes them believe the fake news are real.
Responsibility: Social media, MIMs or users?
Research is showing that news accessed via the internet is becoming increasingly more used as the main way to access news. In the UK and Finland, close to half the participants go to a news app or website for news, while similar numbers in the US and Italy use Social Media as the first place for news (Reuters Institute, 2019). This post has discussed the use of Twitter and WhatsApp for political news and its spread of fake news. However, statistics shows that concern about fake news and lower levels of trust in the media is a global trend. This is despite the differences in how parts of the world attain their political news. Countries that use WhatsApp for political information, as well as countries that use other primary ways of consuming news, are concerned and do experience fake news (Reuters Institute, 2019). This implies that social media and MIMs themselves are not the main issue, but the ways social media and MIMs are being used (Murthy et al., 2016; Vosoughi et al., 2018; Resende et al., 2019; Valenzuela et al., 2019). In other words, where someone gathers their information might not matter as much as from who they get it and their attitudes towards that information.
If one is to look at the research surrounding selective exposure and trust, polarisation and the hostile media phenomenon, these concepts seem to be playing a bigger role than what type of social media and MIMs is used to find the information (Vallone et al., 1985; Tsfati og Cappella, 2003; Hanitzsch et al., 2018; Knudsen et al., 2018; Babaei et al., 2019). However, this does not mean that where one gets the fake news from does not play any role. Research has shown that social media and MIMs can distribute both fake and real news faster and wider than traditional media (Resende et al., 2019; Valenzuela et al., 2019). Yet, for this content to be perceived as ‘real’ or ‘true’ it is shown that the consumers must exhibit some underlying factors in the form of surrounding selective exposure and trust, polarisation and the hostile media phenomenon.
Combating fake news
There have been several suggestions on how to combat fake news. WhatsApp has its own section on how to recognise fake news and how to act if so (WhatsApp, 2019). Facebook is working on three different ways of combating fake news: disrupting economic incentives, building new products and helping users take informed decisions (Facebook, 2017). These actions include having users and third-party fact-checking organisations report fake news on Facebook and working with projects to increase digital literacy. In an analysis of the effectiveness of strategies to combat fake news on social media sites, the results showed that labelling fake news as ‘Rated false’ was the most effective way of making consumers perceive the content as fake (Clayton et al., 2019). However, the labelling of fake news did not have a spill over effect in the way of making consumers more accurately perceive unlabelled fake news content. The strategy of generally warning consumers about the concept of fake news had a minor effect, but the spill over effect in this case negatively impacted the perception all types of news, fake and real (Clayton et al., 2019:19). Another way to regulate fake news online is blacklisting websites. NetSuccess, a Slovakian internet-marketing agency, has been blacklisting fake news websites’ access to advertisement, and therefore their economic gains, by NetSuccess clients. This blacklist has been used by over hundred thousand campaigns (Juhász and Szicherle, 2017:25).
Because fake news is mainly created for two reasons presented above, economic and ideological, it seems most effective to combat fake news in these specific areas. In the economic aspect I suggest continuing to blacklist websites that create fake news content when it comes to advertisement. In terms of social media and MIMs labelling fake news as ‘Rated false’ seems to be the most effective way so far as to stop users from clicking on the articles and generate visitor monetisation. In this case it is also important to rely on third-party fact-checking organisations and not only on users to report the fake news, as research has shown that users’ own biases can affect their perception of what is fake news and not (Vallone et al., 1985; Tsfati og Cappella, 2003; Hanitzsch et al., 2018; Knudsen et al., 2018; Babaei et al., 2019; Clayton et al., 2019).
For the ideological perspective I have argued that it is the consumers who make the final decision to believe fake news or not. While the concept of labelling fake news on social media helped judge specific articles, it did not make the news consumers evaluate unlabelled news more accurately. It is therefore important to focus on education that can enable news consumers to recognise fake news without labels (Clayton et al., 2019:19). The media, companies and government should continue to offer advice on how to accurately judge news content. Education should look to add this concept on the curriculum (Wineburg, 2016) as soon as possible so that young people, who now grow up with online content will be better prepared for fake news when they become old enough to contribute to the public and political environments.
The consequences of fake news online can be argued to be somewhat moderate yet complex. If one perceives the media within its normative role, citizens are dependent on the political information given to them to make political decisions, whether it through voting, activism or voicing their political opinions (Gripsrud, 2007; Skogerbø, 2008). If we consider that the content of the fake news must match the consumers’ own political ideologies, then fake news might not be a problem when it does not align. However, when the content of fake news does align with the consumers’ ideologies, in addition to how social media and MIMs can distribute both fake and real news faster and wider than traditional media (Resende et al., 2019; Valenzuela et al., 2019), it is then concern should appear. Fake news can have the ability to increase polarisation within a population when it aligns with the ideologies of one group than the other.
As possible solutions I suggest combating fake news to block their economic gains, including blacklisting and stop visitor revenue. When it comes to the ideological aspects of fake news, I urge the media, companies and government to continue to offer advice on how to accurately judge news content, in addition to adding this to education curriculums.
Allcott, Hunt, and Matthew Gentzkow. 2017. ‘Social Media and Fake News in The 2016 Election.’ Journal of Economic Perspectives vol. 31(2) pp. 211–236. [Online] [Accessed 29th November 2019] DOI:10.1257/jep.31.2.211.
Bakshy, E., Messing, S. and Adamic, L. (2015). ‘Political science. Exposure to ideologically diverse news and opinion on Facebook.’ Science vol. 348(6239) pp. 1130—1132. [Online] [Accessed 18th December 2019] DOI:10.1145/3287560.3287581
Babaei, M., Chakraborty, A., Kulshrestha, J., Redmiles, E., Cha, M. and Gummadi, K. (2019) ‘Analyzing Biases in Perception of Truth in News Stories and Their Implications for Fact Checking.’ FTA. [Online] [Accessed 29th November 2019] DOI:10.1145/3287560.3287581
BBC (2017) Massive network of fake accounts found on Twitter. [Online] [Accessed 18th December 2019] https://www.bbc.com/news/technology-38724082
Clayton, K., Blair, S., Busam, J. A., Forstner, S., Glance, J., Green, G., … Sandhu, M. (2019) ‘Real solutions for fake news? Measuring the effectiveness of general warnings and fact-check tags in reducing belief in false stories on social media.’ Political Behavior, 1–23. [Online] [Accessed 18th December 2019] DOI:10.1007/s11109-019-09533-0
Facebook (2017) Working to stop misinformation and fake news. [Online] [Accessed 18th December 2019] https://www.facebook.com/facebookmedia/blog/working-to-stop-misinformation-and-false-news
Gil De Zúñiga, H., Correa, T. and Valenzuela, S. (2012) ‘Selective Exposure to Cable News and Immigration in the U.S.: The Relationship Between FOX News, CNN, and Attitudes Toward Mexican Immigrants.’ Journal of Broadcasting & Electronic Media vol. 56 (4) pp. 597-615. [Online] [Accessed 29th November 2019] DOI: 10.1080/08838151.2012.732138
Gripsrud, J. (2007) ‘Mediekultur, mediesamfunn’ (Media culture, media society). 3rd ed., Oslo: Universitetsforlaget AS
Hanitzsch, T., van Dalen, A. and Steindl, N. (2017). ‘Caught in the nexus: A comparative and longitudinal analysis of public trust in the press.’ International Journal of Press/Politics. [Online] [Accessed 29th November 2019] DOI: https://doi.org/10.1177/1940161217740695
Juhász, A. and Szicherle, P. (2017) ‘The political effects of migration – related fake news, disinformation and conspiracy theories in Europe.’ Political Capital [Online] [Accessed 29th November 2019] https://politicalcapital.hu/news.php?article_read=1&article_id=1505
Knudsen, E., Iversen, M. H. and Vatnøy, E. (2018) ‘Mistillit til den andre siden.’ (Distrust in the other side.) Norsk Medietidsskrift, 25(2) pp. 1-20. [Online] [Accessed on 26th November 2019] DOI: 10.18261/ISSN.0805-9535-2018-02-04
Marquart, F., Matthes, J. and Rapp, E. (2016) Selective Exposure in the Context of Political Advertising: A Behavioral Approach Using Eye-Tracking Methodology. International Journal of Communication vol. 10 pp. 2576–2595. [Online] [Accessed 29th November 2019] DOI:1932–8036/20160005
Murthy, D., Powell, A. B., Tinati, R., Anstead, N., Carr, L., Halford, S. J. and Weal, M. (2016) ‘Automation, Algorithms, and Politics| Bots and Political Influence: A Sociotechnical Investigation of Social Network Capital.’ International Journal of Communication Vol 10. [Online] [Accessed 29th November 2019] DOI:
Oltedal, A. (2008) ‘Etikk og journalistikk.’ (Ethics and journalism.) In Von Der Lippe, B. (ed.) ‘Medier, politikk og samfunn’ (Media, politics and society). 5th ed., Oslo: Cappelen Akademiske Forlag, pp. 35—59
Reuters Institute (2019) Reuters Institute Digital News Report 2019. [Online] [Accessed 19th December 2019] https://digitalnewsreport.org/
Resende, G., Melo, P., Reis, C. S., Vasconcelos, M., Almeida, J. M. and Benevenuto, F. (2019) ‘Analyzing Textual (Mis)Information Shared in WhatsApp Groups’. WebSci ’19 Proceedings of the 10th ACM Conference on Web Science. [Online] [Accessed 19th December 2019] DOI:10.1145/3292522.3326029
Sejersted, F. (2008) ‘Ytringsfriheten og informasjonsfriheten’ (Freedom of speech and freedom of information.) In Von Der Lippe, B. (ed.) ‘Medier, politikk og samfunn’ (Media, politics and society). 5th ed., Oslo: Cappelen Akademiske Forlag, pp. 20—34
Skogerbø, E. (2008) ‘Normativ teori, medier og demokrati’ (Normative theory, media and democracy). In Eide, M. (ed.) ‘Medievitenskap: Medier – institusjoner og historie’ (Media science: Media – Institutions and history). Bergen: Fagbokforlaget, pp. 39—52
Skogerbø, E. (2012) ‘Medievitenskapelig analyse – regulering av mediemarkedene’ (Media scientific analysis – regulating the media market). [Online] [Accessed 19th December 2019] https://www.regjeringen.no/globalassets/upload/KUD/Styrer_raad_utvalg/Medieavd elingen/Medievitenskapelig_analyse-regulering_av_mediemarkedene2012.pdf
Tandoc, E. C., Lim, Z. W. and Ling, R. (2018) ‘Defining “Fake News”.’ Digital Journalism, 6(2) pp. 137-153. [Online] [Accessed 29th November 2019] DOI: 10.1080/21670811.2017.1360143
Tsfati, Y. og Cappella, J. N. (2003) ‘Do people watch what they do not trust? Exploring the association between news media skepticism and exposure.’ Communication Research vol. 30(5) pp. 504−529. [Online] [Accessed on 26th November 2019] DOI: https://doi.org/10.1177/0093650203253371
Valenzuela, S., Bachmann, I. and Bargsted, M. (2019) ‘The Personal Is the Political? What Do WhatsApp Users Share and How It Matters for News Knowledge, Polarization and Participation in Chile.’ Digital Journalism. [Online] [Accessed 19th December 2019] DOI: 10.1080/21670811.2019.1693904
Vallone, R. P., Ross, L. and Lepper, M. R. (1985) ‘The hostile media phenomenon: biased perception and perceptions of media bias in coverage of the Beirut massacre.’ Journal of personality and social psychology vol. 49(3) pp. 577—585. [Online] [Accessed 29th November 2019] DOI: https://doi.org/10.1037//0022-35220.127.116.117
Van Aelst, P., Strömbäck, J., Aalberg, T., Esser, F., de Vreese, C., Matthes, J., … and Papathanassopoulos, S. (2017) ‘Political communication in a high-choice media environment: a challenge for democracy?’ Annals of the International Communication Association vol. 41(1) pp. 3—27. [Online] [Accessed on 26th November 2019] DOI: 10.1080/23808985.2017.1288551
Vox (2018) Twitter released 9 million tweets from one Russian troll farm. Here’s what we learned. [Online] [Accessed on 19th December 2019] https://www.vox.com/2018/10/19/17990946/twitter-russian-trolls-bots-election-tampering
Vosoughi, S., Roy, D. and Aral, S. (2018) ‘The spread of true and false news online.’ Science vol. 359(6380) pp. 1146—1151. [Online] [Accessed on 30th November 2019] DOI: https://doi.org/10.1126/science.aap9559
WhatsApp (2019) Tips to help prevent the spread of rumors and fake news. [Online] [Accessed on 19th December 2019] https://faq.whatsapp.com/en/android/26000216/?category=5245250
Wineburg, Sam and McGrew, Sarah and Breakstone, Jo el and Ortega, Teresa. (2016). ‘Evaluating Information: The Cornerstone of Civic Online Reasoning’. Stanford Digital Repository. [Online] [Accessed 19th December 2019] http://purl.stanford.edu/fv751yt5934