Homogeneity trend on social networks changes evolutionary advantage in competitive information diffusion

Abstract

Competitive information diffusion on large-scale social networks reveals fundamental characteristics of rumor contagions and has profound influence on public opinion formation. There has been growing interest in exploring dynamical mechanisms of the competing evolutions recently. Nevertheless, the impacts of homogeneity trend, which determines powerful collective human behaviors, remains unclear. In this paper, we incorporate homogeneity trend into a modified competitive ignorant-spreader-ignorant rumor diffusion model with generalized population preference. Using microscopic Markov chain approach, we first derive the phase diagram of competing diffusion results on Erdös–Rényi graph and examine how competitive information spreads and evolves on social networks. We then explore the detailed effects of homogeneity trend, which is modeled by a rewiring mechanism. Results show that larger homogeneity trend promotes the formation of polarized ‘echo chambers’ and protects the disadvantaged information from extinction, which further changes or even reverses the evolutionary advantage, namely, the difference of stable proportions of the competitive information. However, the reversals may happen only when the initially disadvantaged information has stronger transmission ability, owning diffusion advantage over the other one. Our framework provides profound insight into competing dynamics with homogeneity trend, which may pave ways for further controlling misinformation and guiding public belief systems. Moreover, the reversing condition sheds light on designing effective competing strategies in many real scenarios.

Keywords

• competitive information diffusion
• dynamical evolution
• large-scale social networks
• homogeneity trend