Homophily on social networks changes evolutionary advantage in competitive information diffusion

August 16, 2019 Β· Declared Dead Β· πŸ› New Journal of Physics

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Longzhao Liu, Xin Wang, Yi Zheng, Wenyi Fang, Shaoting Tang, Zhiming Zheng arXiv ID 1908.05992 Category physics.soc-ph Cross-listed cs.SI Citations 30 Venue New Journal of Physics Last Checked 3 months ago
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 population homophily, which determines powerful collective human behaviors, remains unclear. In this paper, we incorporate homophily effects into a modified competitive ignorant-spreader-ignorant (SIS) rumor diffusion model with generalized population preference. Using microscopic Markov chain approach, we first derive the phase diagram of competing diffusion results and examine how competitive information spreads and evolves on social networks. We then explore the detailed effects of homophily, which is modeled by a rewiring mechanism. Results show that homophily promotes the formation of divided "echo chambers" and protects the disadvantaged information from extinction, which further changes or even reverses the evolutionary advantage, i.e., the difference of final proportions of the competitive information. We highlight the conclusion that 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 population homophily, 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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” physics.soc-ph

R.I.P. πŸ‘» Ghosted

Scale-free networks are rare

Anna D. Broido, Aaron Clauset

physics.soc-ph πŸ› Nat. Commun. πŸ“š 988 cites 8 years ago

Died the same way β€” πŸ‘» Ghosted