Coauthorship networks consist of links among groups of mutually connected authors that form a clique. Classical approaches using Social Network Analysis indices do not account for this characteristic. We propose two n...Coauthorship networks consist of links among groups of mutually connected authors that form a clique. Classical approaches using Social Network Analysis indices do not account for this characteristic. We propose two new cohesion indices based on a clique approach, and we redefine the network density using an index of variance of density. We have applied these indices to two coauthorship networks, one comprising researchers that published in Mathematics Education journals and the other comprising researchers from a Computational Modeling Graduate Program. A contextualized and comparative analysis was performed to show the applicability and potential of the indices for analyzing social networks data.展开更多
文摘Coauthorship networks consist of links among groups of mutually connected authors that form a clique. Classical approaches using Social Network Analysis indices do not account for this characteristic. We propose two new cohesion indices based on a clique approach, and we redefine the network density using an index of variance of density. We have applied these indices to two coauthorship networks, one comprising researchers that published in Mathematics Education journals and the other comprising researchers from a Computational Modeling Graduate Program. A contextualized and comparative analysis was performed to show the applicability and potential of the indices for analyzing social networks data.
