Fake news and the spread of misinformation

 
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It’s too soon to say whether Google’s and Facebook’s attempts to clamp down on fake news will have a significant impact. But fabricated stories posing as serious journalism are not likely to go away as they have become a means for some writers to make money and potentially influence public opinion. Even as Americans recognize that fake news causes confusion about current issues and events, they continue to circulate it. A December 2016 survey by the Pew Research Center suggests that 23 percent of U.S. adults have shared fake news, knowingly or unknowingly, with friends and others.

“Fake news” is a term that can mean different things, depending on the context. News satire is often called fake news as are parodies such as the “Saturday Night Live” mock newscast Weekend Update. Much of the fake news that flooded the internet during the 2016 election season consisted of written pieces and recorded segments promoting false information or perpetuating conspiracy theories. Some news organizations published reports spotlighting examples of hoaxes, fake news and misinformation on Election Day 2016.

While much has been written about fake news, scholars have published a limited amount of peer-reviewed research on the topic. Below, Journalist’s Resource has compiled studies that examine fake news and the spread of misinformation more broadly to help journalists better understand the problem and its impacts. Some other resources that may be helpful are the Poynter Institute’s tips on debunking fake news stories and the First Draft Partner Network, a global collaboration of newsrooms, social media platforms and fact-checking organizations that was launched in September 2016 to battle fake news.

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“Social Media and Fake News in the 2016 Election”
Allcott, Hunt; Gentzkow, Matthew. Working paper for the National Bureau of Economic Research, No. 23089, 2017.

Abstract: “We present new evidence on the role of false stories circulated on social media prior to the 2016 U.S. presidential election. Drawing on audience data, archives of fact-checking websites, and results from a new online survey, we find: (i) social media was an important but not dominant source of news in the run-up to the election, with 14 percent of Americans calling social media their “most important” source of election news; (ii) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared eight million times; (iii) the average American saw and remembered 0.92 pro-Trump fake news stories and 0.23 pro-Clinton fake news stories, with just over half of those who recalled seeing fake news stories believing them; (iv) for fake news to have changed the outcome of the election, a single fake article would need to have had the same persuasive effect as 36 television campaign ads.”

 

“Displacing Misinformation about Events: An Experimental Test of Causal Corrections”
Nyhan, Brendan; Reifler, Jason. Journal of Experimental Political Science, 2015. doi: 10.1017/XPS.2014.22.

Abstract: “Misinformation can be very difficult to correct and may have lasting effects even after it is discredited. One reason for this persistence is the manner in which people make causal inferences based on available information about a given event or outcome. As a result, false information may continue to influence beliefs and attitudes even after being debunked if it is not replaced by an alternate causal explanation. We test this hypothesis using an experimental paradigm adapted from the psychology literature on the continued influence effect and find that a causal explanation for an unexplained event is significantly more effective than a denial even when the denial is backed by unusually strong evidence. This result has significant implications for how to most effectively counter misinformation about controversial political events and outcomes.”

 

“Rumors and Health Care Reform: Experiments in Political Misinformation”
Berinsky, Adam J. British Journal of Political Science, 2015. doi: 10.1017/S0007123415000186.

Abstract: “This article explores belief in political rumors surrounding the health care reforms enacted by Congress in 2010. Refuting rumors with statements from unlikely sources can, under certain circumstances, increase the willingness of citizens to reject rumors regardless of their own political predilections. Such source credibility effects, while well known in the political persuasion literature, have not been applied to the study of rumor. Though source credibility appears to be an effective tool for debunking political rumors, risks remain. Drawing upon research from psychology on ‘fluency’ — the ease of information recall — this article argues that rumors acquire power through familiarity. Attempting to quash rumors through direct refutation may facilitate their diffusion by increasing fluency. The empirical results find that merely repeating a rumor increases its power.”

 

“Rumors and Factitious Informational Blends: The Role of the Web in Speculative Politics”
Rojecki, Andrew; Meraz, Sharon. New Media & Society, 2016. doi: 10.1177/1461444814535724.

Abstract: “The World Wide Web has changed the dynamics of information transmission and agenda-setting. Facts mingle with half-truths and untruths to create factitious informational blends (FIBs) that drive speculative politics. We specify an information environment that mirrors and contributes to a polarized political system and develop a methodology that measures the interaction of the two. We do so by examining the evolution of two comparable claims during the 2004 presidential campaign in three streams of data: (1) web pages, (2) Google searches, and (3) media coverage. We find that the web is not sufficient alone for spreading misinformation, but it leads the agenda for traditional media. We find no evidence for equality of influence in network actors.”

 

“Analyzing How People Orient to and Spread Rumors in Social Media by Looking at Conversational Threads”
Zubiaga, Arkaitz; et al. PLOS ONE, 2016. doi: 10.1371/journal.pone.0150989.

Abstract: “As breaking news unfolds people increasingly rely on social media to stay abreast of the latest updates. The use of social media in such situations comes with the caveat that new information being released piecemeal may encourage rumors, many of which remain unverified long after their point of release. Little is known, however, about the dynamics of the life cycle of a social media rumor. In this paper we present a methodology that has enabled us to collect, identify and annotate a dataset of 330 rumor threads (4,842 tweets) associated with 9 newsworthy events. We analyze this dataset to understand how users spread, support, or deny rumors that are later proven true or false, by distinguishing two levels of status in a rumor life cycle i.e., before and after its veracity status is resolved. The identification of rumors associated with each event, as well as the tweet that resolved each rumor as true or false, was performed by journalist members of the research team who tracked the events in real time. Our study shows that rumors that are ultimately proven true tend to be resolved faster than those that turn out to be false. Whilst one can readily see users denying rumors once they have been debunked, users appear to be less capable of distinguishing true from false rumors when their veracity remains in question. In fact, we show that the prevalent tendency for users is to support every unverified rumor. We also analyze the role of different types of users, finding that highly reputable users such as news organizations endeavor to post well-grounded statements, which appear to be certain and accompanied by evidence. Nevertheless, these often prove to be unverified pieces of information that give rise to false rumors. Our study reinforces the need for developing robust machine learning techniques that can provide assistance in real time for assessing the veracity of rumors. The findings of our study provide useful insights for achieving this aim.”

 

“Miley, CNN and The Onion”
Berkowitz, Dan; Schwartz, David Asa. Journalism Practice, 2016. doi: 10.1080/17512786.2015.1006933.

Abstract: “Following a twerk-heavy performance by Miley Cyrus on the Video Music Awards program, CNN featured the story on the top of its website. The Onion — a fake-news organization — then ran a satirical column purporting to be by CNN’s Web editor explaining this decision. Through textual analysis, this paper demonstrates how a Fifth Estate comprised of bloggers, columnists and fake news organizations worked to relocate mainstream journalism back to within its professional boundaries.”

 

“Emotions, Partisanship, and Misperceptions: How Anger and Anxiety Moderate the Effect of Partisan Bias on Susceptibility to Political Misinformation”

Weeks, Brian E. Journal of Communication, 2015. doi: 10.1111/jcom.12164.

Abstract: “Citizens are frequently misinformed about political issues and candidates but the circumstances under which inaccurate beliefs emerge are not fully understood. This experimental study demonstrates that the independent experience of two emotions, anger and anxiety, in part determines whether citizens consider misinformation in a partisan or open-minded fashion. Anger encourages partisan, motivated evaluation of uncorrected misinformation that results in beliefs consistent with the supported political party, while anxiety at times promotes initial beliefs based less on partisanship and more on the information environment. However, exposure to corrections improves belief accuracy, regardless of emotion or partisanship. The results indicate that the unique experience of anger and anxiety can affect the accuracy of political beliefs by strengthening or attenuating the influence of partisanship.”

 

“Deception Detection for News: Three Types of Fakes”
Rubin, Victoria L.; Chen, Yimin; Conroy, Niall J. Proceedings of the Association for Information Science and Technology, 2015, Vol. 52. doi: 10.1002/pra2.2015.145052010083.

Abstract: “A fake news detection system aims to assist users in detecting and filtering out varieties of potentially deceptive news. The prediction of the chances that a particular news item is intentionally deceptive is based on the analysis of previously seen truthful and deceptive news. A scarcity of deceptive news, available as corpora for predictive modeling, is a major stumbling block in this field of natural language processing (NLP) and deception detection. This paper discusses three types of fake news, each in contrast to genuine serious reporting, and weighs their pros and cons as a corpus for text analytics and predictive modeling. Filtering, vetting, and verifying online information continues to be essential in library and information science (LIS), as the lines between traditional news and online information are blurring.”

 

“When Fake News Becomes Real: Combined Exposure to Multiple News Sources and Political Attitudes of Inefficacy, Alienation, and Cynicism”
Balmas, Meital. Communication Research, 2014, Vol. 41. doi: 10.1177/0093650212453600.

Abstract: “This research assesses possible associations between viewing fake news (i.e., political satire) and attitudes of inefficacy, alienation, and cynicism toward political candidates. Using survey data collected during the 2006 Israeli election campaign, the study provides evidence for an indirect positive effect of fake news viewing in fostering the feelings of inefficacy, alienation, and cynicism, through the mediator variable of perceived realism of fake news. Within this process, hard news viewing serves as a moderator of the association between viewing fake news and their perceived realism. It was also demonstrated that perceived realism of fake news is stronger among individuals with high exposure to fake news and low exposure to hard news than among those with high exposure to both fake and hard news. Overall, this study contributes to the scientific knowledge regarding the influence of the interaction between various types of media use on political effects.”

 

“Faking Sandy: Characterizing and Identifying Fake Images on Twitter During Hurricane Sandy”
Gupta, Aditi; Lamba, Hemank; Kumaraguru, Ponnurangam; Joshi, Anupam. Proceedings of the 22nd International Conference on World Wide Web, 2013. doi: 10.1145/2487788.2488033.

Abstract: “In today’s world, online social media plays a vital role during real world events, especially crisis events. There are both positive and negative effects of social media coverage of events. It can be used by authorities for effective disaster management or by malicious entities to spread rumors and fake news. The aim of this paper is to highlight the role of Twitter during Hurricane Sandy (2012) to spread fake images about the disaster. We identified 10,350 unique tweets containing fake images that were circulated on Twitter during Hurricane Sandy. We performed a characterization analysis, to understand the temporal, social reputation and influence patterns for the spread of fake images. Eighty-six percent of tweets spreading the fake images were retweets, hence very few were original tweets. Our results showed that the top 30 users out of 10,215 users (0.3 percent) resulted in 90 percent of the retweets of fake images; also network links such as follower relationships of Twitter, contributed very little (only 11 percent) to the spread of these fake photos URLs. Next, we used classification models, to distinguish fake images from real images of Hurricane Sandy. Best results were obtained from Decision Tree classifier, we got 97 percent accuracy in predicting fake images from real. Also, tweet-based features were very effective in distinguishing fake images tweets from real, while the performance of user-based features was very poor. Our results showed that automated techniques can be used in identifying real images from fake images posted on Twitter.”

 

“The Impact of Real News about ‘Fake News’: Intertextual Processes and Political Satire”
Brewer, Paul R.; Young, Dannagal Goldthwaite; Morreale, Michelle. International Journal of Public Opinion Research, 2013. doi: 10.1093/ijpor/edt015.

Abstract: “This study builds on research about political humor, press meta-coverage, and intertextuality to examine the effects of news coverage about political satire on audience members. The analysis uses experimental data to test whether news coverage of Stephen Colbert’s Super PAC influenced knowledge and opinion regarding Citizens United, as well as political trust and internal political efficacy. It also tests whether such effects depended on previous exposure to The Colbert Report (Colbert’s satirical television show) and traditional news. Results indicate that exposure to news coverage of satire can influence knowledge, opinion, and political trust. Additionally, regular satire viewers may experience stronger effects on opinion, as well as increased internal efficacy, when consuming news coverage about issues previously highlighted in satire programming.”

 

“With Facebook, Blogs, and Fake News, Teens Reject Journalistic ‘Objectivity’”
Marchi, Regina. Journal of Communication Inquiry, 2012. doi: 10.1177/0196859912458700.

Abstract: “This article examines the news behaviors and attitudes of teenagers, an understudied demographic in the research on youth and news media. Based on interviews with 61 racially diverse high school students, it discusses how adolescents become informed about current events and why they prefer certain news formats to others. The results reveal changing ways news information is being accessed, new attitudes about what it means to be informed, and a youth preference for opinionated rather than objective news. This does not indicate that young people disregard the basic ideals of professional journalism but, rather, that they desire more authentic renderings of them.”

 

Keywords: alt-right, credibility, truth discovery, post-truth era, fact checking, news sharing, news literacy, misinformation, disinformation

    Writer: | Last updated: January 9, 2017

     

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