Chapter I: Introduction
1.5 Literature Review
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1.5 Literature Review
Over the past years, scholars have been focusing on the study of fake news due to the impact it has brought. Research on fake news can be organized into different categories based on their goals and approaches.
The first category of fake new studies consists of the research aiming to define fake news. Indeed, fake news are not something new or unprecedented. Even before the apparition of social media, traditional news media already showcased unverified or misleading information (Shu and al. 2017). However, with the rise of entertainment media and social media, fake news has become more diverse and complex. For instance, some scholars consider satirical imitations of real news, such as TV shows and satirical newspapers, as a form of fake news as they distort the reality and can alter people’s judgment (Balmas 2012, Berkowitz and Schwartz 2016). Other scholars fixate on the notion of “fake”. For instance, Wardle contends that “fake” can fall into seven different categories: satire or parody (attend to fool the audience but not to cause harm), false connection (i.e., when the headlines do not support the content), misleading content (aiming to frame an issue or individual), false context (the information is genuine but not the context), imposter content (the information is genuine but has been impersonated), manipulated content, and fabricated content (the content is entirely fake and aims to harm) (Wardle 2017).
The second category comprises the studies focusing on the influence of fake news on citizens’ knowledge, opinion, and political trust. These studies reveal that fake news disturbs people’s perceptions of the political system and can generate a feeling of distrust among citizens toward the political elites (Balmas 2012, Brewer and al. 2013).
Through her analysis of the 2006 Israeli elections campaign, Meital Balmas demonstrated that voters who were exposed to fake news tended to distrust candidates
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and the political system (Balmas 2012). Her study also points out that this trend increases when viewers are more accustomed to seeing fake news than real news (Balmas 2012). In their analysis of news media coverage of a satirical show discussing American politics, Brewer and al. denoted that the way traditional media address fake news also impacts people’s opinion (Brewer and al. 2013). As their study points out exposure to fake news (even via traditional media) generates political distrust and misconceptions of decision-making processes (Brewer and al. 2013). Other researchers study fake news’ impact among the different age groups. For example, based on her study of 61 American teenagers, Regina Marchi pointed out that the main reasons behind fake news’ success among the younger generation is their preference for fake news’ subjectivity and mistrust toward mainstream news media’s objectivity (Marchi 2012).
The third category encompasses the mechanisms behind the creation and propagation of fake news. For example, Shu and al. pointed out that not only new technologies have lowered the cost to produce fake news, they also levitated the spread (Shu and al. 2017). The scholars further stress the importance of social bots, which are social media accounts controlled by a computer (Shu and al. 2017). According to a study of the University of Oxford, during the 2016 US elections, the social media Twitter was flooded by 19 million bots publishing content in support of either candidate.24 Still there are other research trying to explain how fake news spread through a new network of alternative sources of information called the “Fifth Estate,”
which is formed by blogs, social media pages, satirical shows, and other alternative sources of information (Dutton 2009, Berkowitz and Schwartz 2016). Finally, some
24 Oxford Internet Institute, “Resource for Understanding Political Bots,” The Computational Propaganda Project, November 18, 2016.
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studies point out that fake news spread through partisan media as they use them to push the popularity of certain issues such as the economy, international relations, or religion (Vargo and al. 2017). Besides, according to Vargo and al., during the 2016 US election, partisan media relied on fakes news to attack the other candidate (Vargo and al. 2017).
Finally, since fake news has become a major concern, many researchers have been putting effort to define the best approaches to identify and fight them. Some scholars recommend a linguistic approach to develop automatic fake news detection (Wang 2017). This idea derives from the use of “clickbait,” a common characteristics of fake news to attract the attention of audience by sensational headlines (Chen, and al. 2015).
Regarding the way of preventing the propagation of fake news, some propose to combat them by reducing their economic attractiveness (Bakir and McStay 2017). For example, convincing major advertising associations to stop supporting websites that display fake content might be a solution to turn down the economic incentive behind the production of fake news (Bakir and McStay 2017). Among the studies in pursuit of preventing the propagation of fake news on social media, one of the possible solutions proposed is to identify and block the accounts that share fake news and try to persuade other users of their veracity (Shu and al. 2018). Another solution would be to maximize the spread of real news on social media to mitigate users’ exposure to fake content (Shu and al. 2018).
Still others suggest monitor social bots as a way to combat fake content at an early stage (Shao and al. 2017). Since a few social bots suffice to amplify the spreading of fake news, taking these accounts down could drastically reduce their propagation (Shao and al. 2017).
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