Measuring the Ease of Communication in Bipartite Social Endorsement Networks

Abstract

In this work, complex weighted bipartite social networks are developed to efficiently analyze, project and extract network knowledge. Specifically, to assess the overall ease of communication between the different network sub-clusters, a proper projection and measurement method is developed in which the defined measurement is a function of the network structure and preserves maximum relevant information. Using simulations, it is shown how the introduced measurement correlates with the concept of political polarization, after which the proposed method is applied to Facebook networks to demonstrate its ability to capture the polarization dynamics over time. The method successfully captured the increasing political polarization between the Alternative für Deutschland's (AfD) supporters and the supporters of other political parties, which is in line with previous studies on the rise of the AfD in Germany's political sphere. CCS CONCEPTS • Networks → Social media networks; Network simulations; • Human-centered computing → Social network analysis; Social networking sites; • General and reference → Metrics; Estimation;

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