"Analyzes the spread of information on social media (Twitter) and purpose a strategy based on epidemiological models. It is well known that social media represent a strong tool to spread news and, in particular, fake news, due to the fact that they are free and easy to use. First, we propose an algorithm to create a proper dataset in order to employ the ignorants–spreaders–recovered epidemiological model. Then, we show that to use this model to study the diffusion of real news, parameter estimation is required. We show that it is also possible to accurately predict the evolution of news spread and its peak in terms of the maximum number of people who share it and the time when the peak occurs trough a process of data reduction, i.e., by using only a part of the built dataset to optimize parameters. Numerical results based on the analysis of real news are also provided to confirm the applicability of our proposed model and strategy." [ABSTRACT FROM AUTHOR]

"Easy access to equipment, software, and platforms to create, distribute, and provide access to fake news stories has exacerbated the problem of fake news, making for a large number of highly biased sources that are reaching the mainstream through social networks. The economics of emotion theory proposes that fake news headlines are created to evoke emotional responses in readers that will cause them to interact with the article in a way that allows the creator to make a profit (through clicking on the link to the full article, by sharing the article, etc.). This mixed methods study investigates the process by which individuals experience discrete emotional reactions to fake news headlines, and how these emotions contribute to the perpetuation of fake news through sharing behaviors."

"Several studies have examined the consumption and spread of fake news on social media. Two notable gaps, though, exist in the extant literature. First, prior research has focused on the political orientation of users while ignoring the broader context of sharing, namely the perceived political orientation of their social media peers. Second, there is limited insight about how user states, especially those related to their judgment abilities, influence the critical evaluation of fake news on social media. This paper addresses these gaps."

"This study found that the presence of a fake news flag triggered increased cognitive activity and users spent more time considering the headline. However, the flag had no effect on judgments about truth; flagging headlines as false did not influence users’ beliefs. A post hoc analysis shows that confirmation bias is pervasive, with users more likely to believe news headlines that align with their political opinions. Headlines that challenge their opinions receive little cognitive attention (i.e., they are ignored) and users are less likely to believe them." [ABSTRACT FROM AUTHOR]