Considering weights in real social networks: A review
Michele Bellingeri, Danièle Bevacqua, F. Sartori, Massimiliano Turchetto, Francesco Scotognella, Roberto Alfieri, Ngoc-Kim-Khanh Nguyen, Thanh-Tan Le, Quang Nguyen, Davide Cassi
Abstract
Network science offers powerful tools to model complex social systems. Most social network science research focuses on topological networks by simply considering the binary state of the links, i.e., their presence or absence. Nonetheless, complex social systems present heterogeneity in link interactions (link weight), and accounting for this heterogeneity, it is mandatory to design reliable social network models. Here, we revisit the topic of weighted social networks (WSNs). By summarizing the main notions, findings, and applications in the field of WSNs, we outline how WSN methodology may improve the modeling of several real problems in social sciences. We are convinced that WSNs may furnish ideas and insights to open interesting lines of new research in the social sciences.