Fashion, cooperation, and social interactions

• Published in: PloS one 2013-01, Vol.8 (1), p.e49441-e49441
• Main Authors: Cao, Zhigang, Gao, Haoyu, Qu, Xinglong, Yang, Mingmin, Yang, Xiaoguang
• Format: Article
• Language: English
• Subjects: Archives & records; Biology; Cell culture; Cellular automata; Cellular communication; Competition; Computer Science; Computer Simulation; Cooperation; Cooperative Behavior; Culture; Economic models; Equilibrium; Fashion; Game theory; Humans; Impact analysis; Information systems; Interpersonal Relations; Laboratories; Mathematics; Phase transitions; Philosophers; Physics; Simulation; Social and Behavioral Sciences; Social aspects; Social behavior; Social factors; Social interactions; Social networks; Social organization; Society; Synchronism; Synchronization; Systems science
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0049441

Fashion plays such a crucial rule in the evolution of culture and society that it is regarded as a second nature to the human being. Also, its impact on economy is quite nontrivial. On what is fashionable, interestingly, there are two viewpoints that are both extremely widespread but almost opposite: conformists think that what is popular is fashionable, while rebels believe that being different is the essence. Fashion color is fashionable in the first sense, and Lady Gaga in the second. We investigate a model where the population consists of the afore-mentioned two groups of people that are located on social networks (a spatial cellular automata network and small-world networks). This model captures two fundamental kinds of social interactions (coordination and anti-coordination) simultaneously, and also has its own interest to game theory: it is a hybrid model of pure competition and pure cooperation. This is true because when a conformist meets a rebel, they play the zero sum matching pennies game, which is pure competition. When two conformists (rebels) meet, they play the (anti-) coordination game, which is pure cooperation. Simulation shows that simple social interactions greatly promote cooperation: in most cases people can reach an extraordinarily high level of cooperation, through a selfish, myopic, naive, and local interacting dynamic (the best response dynamic). We find that degree of synchronization also plays a critical role, but mostly on the negative side. Four indices, namely cooperation degree, average satisfaction degree, equilibrium ratio and complete ratio, are defined and applied to measure people's cooperation levels from various angles. Phase transition, as well as emergence of many interesting geographic patterns in the cellular automata network, is also observed.