In the last decade, Social Media Platforms have become our main communication hub, encompassing both our personal and our public life. As online social networks have established themselves as important sources or information, they have rapidly changed the landscape of the news media ecosystem on a global scale. News is no longer exclusively broadcast by established sources. Within the participatory environment of these platforms, new opinion leader often actively creates and disseminate news without the restrictions posed upon classical media channels, and often reach large audiences. In this PhD project, we want to investigate how the structural and functional characteristics of online communication networks influence the circulation of news with a focus on disinformation and more broadly junk news. We further want to investigate how such unreliable information diffuses differently across heterogeneously formed communities and characterize the behavior surrounding their reception. We will use methodologies coming from network science, data science and complexity science, integrating the insight about the role taken users that can be obtained by the analysis of the communication network and the associated spreading dynamics with insight about the stance of those users that be automatically extracted using NLP methods.