multiplexity

Multiplexity is the property of having multiple kinds of connections between the same set of actors, or the use of multiple layers to represent different types of relations in a network. In sociology, multiplexity describes how individuals may be linked by several simultaneous ties—such as friendship, kinship, work, or neighborhood—between the same pair of people. In network science, this idea is formalized by multiplex or multilayer networks, where the same nodes participate in several layers, each corresponding to a distinct relation type.

Each layer encodes a relation type; edges may be binary or weighted. The interdependencies across layers can influence dynamics not visible in a single-layer view. Researchers study multiplexity by examining edge overlap (the extent to which a pair is connected in multiple layers) and by analyzing interlayer coupling, which captures how the presence of a connection in one layer affects connectivity in others. The multiplexity of a node pair can be summarized by a multiplexity score, and the full system is often represented by a set of adjacency matrices or by a tensor.

High multiplexity can enhance information diffusion, trust, and social capital but can also transmit shocks across layers, impacting resilience. Layer interactions shape community structure, centrality, and the robustness of networks to failures or removals.

Applications span sociology, organizational studies, epidemiology, transportation, and communication networks. Multiplex models provide a more realistic framework for analyzing complex social systems where multiple kinds of ties coexist.