Exploring the effect of reinvention on critical mass formation and the diffusion of information in a social network

Abstract

Widely used information diffusion models are based on the assumption that exposure to information, like exposure to a virus, is enough for it to spread. However, the diffusion of information is more complex and involves an array of decisions regarding whether to consume the information received, and upon consumption, whether to pass it on to others. Using an agent-based simulation run on an actual network graph, we model a realistic information consumption and transmission process. The model builds upon the combination of two prominent social theories: diffusion of innovations and critical mass theory. We introduce the concept of reinvention, the modification of information, and investigate its effect on both critical mass formation and on the overall diffusion of information in the social network. Results show that network topology is crucial while traditional concepts such as ‘inflection point’ or ‘early adopters’ are of secondary importance. Although reinvented information requires more nodes to reach critical mass, it prolongs the diffusion of information past the inflection point so that information reaches a larger final audience, while also exhibiting accelerated production functions. Reinvention is found to have a prominent effect when transmitted via weak ties, thus allowing information to undergo an evolutionary process that contributes to an overall higher value of information, collective outcome, in the network.