  We study the effects of conformity, the tendency of humans to imitate locally
common behaviors, in the evolution of cooperation when individuals occupy the
vertices of a graph and engage in the one-shot Prisoner's Dilemma or the
Snowdrift game with their neighbors. Two different graphs are studied: rings
(one-dimensional lattices with cyclic boundary conditions) and scale-free
networks of the Barabasi-Albert type. The proposed evolutionary-graph model is
studied both by means of Monte Carlo simulations and an extended
pair-approximation technique. We find improved levels of cooperation when
evolution is carried on rings and individuals imitate according to both the
traditional pay-off bias and a conformist bias. More important, we show that
scale-free networks are no longer powerful amplifiers of cooperation when fair
amounts of conformity are introduced in the imitation rules of the players.
Such weakening of the cooperation-promoting abilities of scale-free networks is
the result of a less biased flow of information in scale-free topologies,
making hubs more susceptible of being influenced by less-connected neighbors.
