Modern societies understand the world, manifest different viewpoints, and test their objectiveness by exchanging information through direct communication or, in more recent years, through online social networks. On a larger scale, this process may also create consensus and mitigate social friction through public debate, two essential aspects of a healthy democracy. Information diffusion is often represented by pieces of information (e.g., news, scientific, or historical facts) that spread through a network. As for the network, that consists of interacting entities such as individuals, institutions (e.g., governments, authorities, or other organizations), and private entities (e.g., media, marketing agencies). The Internet era has offered new means to produce and share information through large-scale online social networks. The disposition of large amounts of data coming from diffusion traces has helped scientific research improve our understanding of diffusion processes arising in various disciplines, including sociology, epidemiology, marketing, and computer system security. However, the democratization of content creation and sharing has not been adequately coupled with effective (self-, collective, or automatic) moderation, correction, and filtering mechanisms. Consequently, the explosive volume of the available content brings forward huge challenges regarding the human capacity to process that fast-paced and gigantic information stream as well as regarding the technical aspects of data management. Our daily information diet tends to promote the variety in the content we consume to the expense of its precision and detail. During moments of crisis, the scarcity of trustworthy information and lack of time to analyze it lead to the proliferation of false rumors. There are also various psychological factors that impact the way we participate in this exchange. For instance, people get influenced by others, but also tend to search and recall information and facts that align with their already formed belief system (confirmation bias). Furthermore, users interact preferably with people of similar profiles and opinions (homophily), a tendency that greatly reduces the heterogeneity of the user’s perceived public debate. In addition, members of any online group receive social pressure to conform to a group’s beliefs; that tends to radicalize opinions and allow questionable ideas to gain momentum (echo chambers). Then, the relative isolation of small online communities may lead them to believe in false rumors, even create a false consensus against what is considered as verifiable by the majority of society. The situation may get considerably aggravated in periods of political tension where polarization and partisanship grow in well-segregated groups that reduce significantly their exposure to counterarguments. Rumor spreading and control. There are many types of misinformation: bad or “yellow” journalism, fake news, rumors and unverified information, hoaxes, and others (for a discussion on the taxonomy see [1]).