Giant cluster formation and integrating role of bridges in social diffusion

Abstract Research Summary In social networks, isolated subgroups often aggregate into a massively connected subgroup, or a giant cluster, when bridges are built across subgroups. To understand the roles of bridges in integrating subgroups, we develop models focusing on the percentage of bridges among all ties. When it is below 1%, diffusion does not affect many individuals because the system is merely a collection of fragmented subgroups. Near 1%, however, we find that a slight increase in the percentage of bridges leads to sudden widespread diffusion across many subgroups. This dramatic change stems from a threshold‐like structural characteristic of the network whereby previously fragmented subgroups come together abruptly. Our findings suggest that this integrating role of bridges is an important piece missing from the literature on small‐world networks. Managerial Summary Our findings suggest that the formation of a giant cluster could be a structural precondition for large‐scale diffusion. Detection of such clusters may allow prognostication of the possibility of large‐scale diffusion. With the rise of social media and the availability of large amounts of social network data, the ability to detect giant clusters seems to be more attainable than in the past; such an ability would be a source of competitive advantage. We describe methods of detecting giant clusters and analyzing their structural properties using readily available social network data. With these methods, entrepreneurs and established firms can stimulate user adoption by targeting massive clusters of aggregated subgroups and spreading viral messages about their new products or services throughout the clusters.