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Shortly after the first COVID-19 cases became apparent in December 2020,rumors spread on social media suggesting a connection between the virus and the5G radiation emanating from the recently deployed telecommunications network.In the course of the following weeks, this idea gained increasing popularity,and various alleged explanations for how such a connection manifests emerged.Ultimately, after being amplified by prominent conspiracy theorists, a seriesof arson attacks on telecommunication equipment follows, concluding with thekidnapping of telecommunication technicians in Peru. In this paper, we studythe spread of content related to a conspiracy theory with harmful consequences,a so-called digital wildfire. In particular, we investigate the 5G and COVID-19misinformation event on Twitter before, during, and after its peak in April andMay 2020. For this purpose, we examine the community dynamics in complextemporal interaction networks underlying Twitter user activity. We assess theevolution of such digital wildfires by appropriately defining the temporaldynamics of communication in communities within social networks. We show that,for this specific misinformation event, the number of interactions of the usersparticipating in a digital wildfire, as well as the size of the engagedcommunities, both follow a power-law distribution. Moreover, our researchelucidates the possibility of quantifying the phases of a digital wildfire, asper established literature. We identify one such phase as a criticaltransition, marked by a shift from sporadic tweets to a global spread event,highlighting the dramatic scaling of misinformation propagation.

Harmful Conspiracies in Temporal Interaction Networks: Understanding the Dynamics of Digital Wildfires through Phase Transitions