Archives: Research

Since the 2016 US presidential election, there has been a growing concern against the rise of misinformation. This report looks into the quality and quantity of information flows during the 2018 US midterm election campaign, focusing on two new forms of media – "fake news" and political ads on Facebook. An examination of fake news sites finds there has been a substantial decline in the proportion of Americans who visited fake news sites in 2018 as compared to 2016. The report's data also revealed that exposure to Facebook political ads was limited and relative to a subset of targeted users who frequently used Facebook. In conclusion, the report also provides new evidence of how Americans frequently believe fake and hyper-partisan news and misperceptions promoted by the elites on social media during the campaign.

Crowdsourced judgments about the quality of news sources may effectively marginalize false news stories and other kinds of online misinformation. According to researchers, the crowdsourcing approach could work especially well in marginalising false news stories—for instance by building audience judgments into an algorithm ranking stories by quality. Crowdsourcing would probably be less effective, however, if a social media site were trying to build a consensus about the very best news sources and stories.

The rise of fake news has led to growing concern about the prevalence and effects of misinformation in political campaigns particularly in the aftermath of the 2016 US presidential elections. This study uses an original survey to link individual-level characteristics associated with sharing false articles during the 2016 US presidential campaign on Facebook. 

This study is one of the largest analyses to date on the spread of fake news on Twitter during and after the 2016 US election campaign. It used tools and mapping methods from Graphika, a social media intelligence firm, to study more than 10 million tweets from 7,00,000 Twitters accounts linked to more than 600 fake and conspiracy news outlets. The study also focuses on fake and conspiracy news both before and after the election in order to measure the evolving structure of the fake news structure since November 2016.

In a 2018 study by Stanford University, a measure of trends in the diffusion of content was undertaken from 570 news websites and 10,240 fake news stories across Facebook and Twitter between January 2015 and July 2018. It was found that user interactions with false news stories was on the rise till 2016 on both platforms. However, post Facebook’s efforts to limit the diffusion of misinformation after the US 2016 election scandal, interactions with false stories fell sharply on the platform. On the other hand, Twitter continued to see a rise in its user engagement with false stories. 

This working paper sheds light on the demographic and situational factors that influence the likelihood of sharing fake news on social media platforms. The paper uses a representative sample of 1,002 US adults from the Pew Research Center for the study. The research revealed the relationships between the probability of sharing fake news articles and predictor variables such as demographics, and situational factors. It offered evidence on the prototype user who contributed to the spread of misinformation and what that implied for professional journalism. 

The study investigated the differential diffusion of all the verified true and false news stories on Twitter during the period 2006-2017. The data comprised 1,26,000 stories tweeted by 3 million people more than 4.5 million times. The news was classified into true or false using information from six fact-checking organisations. It was found that false news diffused farther, faster, deeper and more broadly than the truth in all categories of information and its effects were more were more pronounced for false political news. People were more likely to share false news due to its novelty. It was also found that robots accelerated the spread of true and false news at the same rate, implying that false news spread rapidly not because humans but robots spread it.

To help counter the rapid spread of online misinformation, Cambridge University researchers developed a "fake news game" in which participants were tasked with creating a news articles about a strongly politicised issue using misinformation tactics from the perspectives of different types of fake news producers. The game was pilot tested in a randomised field study (N=95) in a public high school setting. The results indicted that educational games like this may be a promising way to inoculate the public against fake news.
 

This Reuters Institute for the Study of Journalism (RISJ) factsheet provides top-level usage statistics for the most popular sites that independent fact-checkers and other observers have identified as publishers of fake news and online disinformation in France and Italy. The study is based on a sample of 300 websites in each country that independent fact-checkers have identified as publishers of fake news, focusing on a measure of the sites' reach, attention and number of Facebook interactions. The study provides context by comparing these figures with data from an equivalent selection of widely-used French and Italian news brands. 

The idea of an "echo chamber" extends to tendencies towards exposure to specific political content which is likely to extend to misinformation further exacerbated by social media platforms. This report tests this prediction using data found on fake news combined with survey responses to find that 1 in 4 Americans visited fake news sites from October 7 to November 14, 2016. However, this consumption of fake news was heavily concentrated among a small group of conservative leaning individuals. The report also finds Facebook to be a major vector of exposure to fake news and that its fact-checks almost never reached its users'.