Conspiracy Network in Facebook Pages: An Agent Based Model of Misleading Information in an Echo Chamber

The emergence and development of conspiracy phenomena within the digital space is broadly studied in the literature. The spread of junk or misleading information online is amplified by the increasing use of Social Networks and social media. Specifically on Facebook, there are networks that are specialized in disseminating information from unofficial sources. The aim of this work is to create an agent-based computational model capable of describing and analysing the structure and the development of a conspiracy echo-chamber within Facebook. We map and analyse the development and characteristics of a conspiracy echo-chamber within Facebook, through the study of interactions of articles from unofficial sources within the social network. Then, we explore the variation of the network structure in relation to the variation of certain properties of the articles. A set of preferential sources of information emerge, as if they are somehow being credited by the conspiracy public as references for the dissemination of "informative" content. We also find that there is a polarized bubble of content and users with respect to conspiracy-mindedness. We show that there are pages that have a preferential role within the network as opinion leaders in the conspiracy bubble. Moreover, we also show that there are elements that distinguish many of the analyzed contents, namely political orientation and hate speech. Finally, we highlight that the grounded approach is very useful in the classification process because approaching classification without a-priori categories to be identified in the text make it possible for issues and specific interpretative codes to emerge.