English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

The massive diffusion of online social media allows for the rapid anduncontrolled spreading of conspiracy theories, hoaxes, unsubstantiated claims,and false news. Such an impressive amount of misinformation can influencepolicy preferences and encourage behaviors strongly divergent from recommendedpractices. In this paper, we study the statistical properties of viralmisinformation in online social media. By means of methods belonging to ExtremeValue Theory, we show that the number of extremely viral posts over timefollows a homogeneous Poisson process, and that the interarrival times betweensuch posts are independent and identically distributed, following anexponential distribution. Moreover, we characterize the uncertainty around therate parameter of the Poisson process through Bayesian methods. Finally, we areable to derive the predictive posterior probability distribution of the numberof posts exceeding a certain threshold of shares over a finite interval oftime.

On the statistical properties of viral misinformation in online social media