🤖 AI Summary
This study addresses the propagation of rumors in networks with community structure by proposing a modeling paradigm that leverages high intra-community connectivity and low inter-community connectivity to capture real-world scenarios—such as groups of traders within investment firms—where information spreads rapidly within groups but is constrained across group boundaries. By constructing a community-structured network model and analyzing its diffusion dynamics, the research demonstrates that such networks exhibit markedly different patterns in both the extent and speed of rumor spread compared to small-world or random networks. The findings reveal that while network topology exerts only a subtle influence, its effect is nonetheless non-negligible. This work thus provides a theoretically grounded and structurally realistic framework for modeling and predicting information diffusion in socially embedded contexts.
📝 Abstract
Many real-world networks have the characteristic that they are comprised of distinct groups or communities whose members contain many links within the community but with fewer connections to others. It is important to accurately model these types of networks to correctly predict the outcome of important spreading processes such as disease transmission, or the flow of information etc. Our motivating example is a network of traders within several investment institutions such as hedge funds. We assume an idealised scenario where traders within the same institution have many contacts and can share information quickly and easily but have fewer contacts to traders in other institutions, relying on personal networks, allowing for information to flow easily within a community and less-so between communities. In this paper we investigate a particular spreading process, the spread of a rumour, on a community based network that is characterised by two parameters; the within-group connectivity, and the between-group connectivity. We show that such networks have different characteristics to small-world or random networks that are often used to model the types of systems and that the network topology has a small but not insignificant effect on the spread of rumours on the network.