Considering weights in real social networks: A review

Frontiers in Physics

Physics

Q. Nguyen¹  F. Sartori²  F. Scotognella³  N. K. K. Nguyen⁴  T. T. Le⁵  R. Alfieri⁶  M. Bellingeri⁶  D. Cassi⁶  M. Turchetto⁶  D. Bevacqua⁷ 

[1] 10, Institute of Fundamental and Applied Sciences, Duy Tan University, Ho Chi Minh City, Vietnam;11, Faculty of Natural Sciences, Duy Tan University, Da Nang, Vietnam;4, Department of Sociology, Karlsruhe Institute of Technology, Karlsruhe, Germany;5, Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany;6, Dipartimento di Fisica, Politecnico di Milano, Milano, Italy;Center for Nano Science and Technology@PoliMi, Istituto Italiano di Tecnologia, Milan, Italy;8, Faculty of Basic Science, Van Lang University, Ho Chi Minh City, Vietnam;9, John von Neumann Institute, Vietnam National University, Ho chi minh City, VietNam;Dipartimento di Scienze Matematiche, Fisiche e Informatiche, Università di Parma, Parma, Italy;INFN, Gruppo Collegato di Parma, Parma, Italy;PSH, UR 1115, French National Research Institute for Agriculture, Food, and the Environment (INRAE), Avignon, France;

关键词: social networks;    weighted networks;    weighted network analysis;    network science;    social physics;   

DOI  :  10.3389/fphy.2023.1152243

 received in 2023-01-27, accepted in 2023-03-13,  发布年份 2023

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

Unknown   
Copyright © 2023 Bellingeri, Bevacqua, Sartori, Turchetto, Scotognella, Alfieri, Nguyen, Le, Nguyen and Cassi.