Competitive Information Spreading on Modular Networks

Satoshi Furutani, Toshiki Shibahara, Mitsuaki Akiyama, Masaki Aida

Abstract: Information spreading on social networks is one of the most important topics in network science and has long been actively studied. However, most studies only focus on the spread of a single piece of information on random networks, even though information spreading in the real world is much more complicated, involving a complex topology structure and interactions between multiple information. Therefore, in this paper, we model the competitive information spreading on modular networks and investigate how the community structure affects competitive information spreading in two spreading scenarios: sequential and simultaneous. In the sequential spreading scenario, we find that the community structure has little effect on the final prevalence but affects the spreading process (time evolution of the prevalence). In contrast, in the simultaneous spreading scenario, we find that community structure has a strong effect on not only the spreading process but also the final prevalence. Specifically, two competing pieces of information cannot coexist and one drives out the other on a non-modular network, whereas they can coexist in different communities on a modular network. Our results suggest that the effect of community structure cannot be ignored in the analysis of competitive spreading (especially, simultaneous spreading) of multiple information.