Dynamics of competing ideas in complex social systems

Abstract

Individuals accepting an idea may intentionally or unintentionally impose influences in a certain neighborhood area, making other individuals within the area less likely or even impossible to accept other competing ideas. Depending on whether such influences strictly prohibit neighborhood individuals from accepting other ideas or not, we classify them into exclusive and non-exclusive influences, respectively. Our study reveals for the first time the rich and complex dynamics of two competing ideas with neighborhood influences in scale-free social networks: depending on whether they have exclusive or non-exclusive influences, the final state varies from multiple coexistence to founder control to exclusion, with different sizes of population accepting each of the ideas respectively. Such results provide insights helpful for better understanding the spread (and the control of spread) of ideas in human society.

23 pages, 13 figures, accepted for publication in New Journal of Physics

References in corpus (3)

• On the Role of Zealotry in the Voter Model
• Threshold effects for two pathogens spreading on a network
• Epidemic Dynamics of Interacting Two Particle Species on Scale-free Networks

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