AUTHOR=Mazzeo Valeria , Rapisarda Andrea 

TITLE=Investigating Fake and Reliable News Sources Using Complex Networks Analysis

JOURNAL=Frontiers in Physics

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2022.886544

DOI=10.3389/fphy.2022.886544

ISSN=2296-424X

ABSTRACT=The rise of disinformation in the last years has shed light on the presence of bad actors that every day produce and spread misleading content. Looking at the characteristics of these actors has become therefore crucial for gaining better knowledge on the phenomenon of disinformation in order to fight it.
This study seeks to understand how these actors, meant here as unreliable news websites, differ from reliable ones.  
With this aim, we investigated some well-known fake and reliable news sources and their relationships, using a network growth model based on the overlap of their audience. Then, we peered into the news sites' sub-networks and their structure, finding that unreliable news sources sub-networks are overall disassortative and have a low-medium clustering coefficient, indicative of a higher fragmentation.
The k-core decomposition allowed us to find the coreness value for each node in the network, identifying the most connectedness sites communities and revealing the structural organisation of the network, where the unreliable websites tend to populate the inner shells. By analysing WHOIS information it also emerged that unreliable websites have generally a newer registration date and shorter-term registrations compared to reliable websites. The results on political leaning of the news sources show extremist news sources of any political leaning are generally mostly responsible of producing and spreading disinformation.