Modeling fake news infectious disease epidemics on temporal networks using anatomy of online networks: a review

In recent years, the term “social network” has come to refer to the virtual communities of user’s websites such as Facebook, Twitter, and others. People in a social network have online social contacts with their relatives, coworkers, friends, and so on, using different platforms at different frequencies. As a result, the network approach can be used to study pathogen spread in a contact network or rumor spread in an online social network. Evidently, this is the type of network in which we are interested in understanding and modeling the processes involved in the spread of news, the most of which is spread through social online contact between individuals. This social network is illustrated with temporal networks that differ to static networks. The open platform Hoaxy is used. It allows for large-scale, systematic research into the spread of fake news (misinformation) and real news (fact-checking) on Twitter during the 2016 US Presidential Election. This paper reviews simple and complex mathematical epidemiological models with temporal networks and discuss future work developments.