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Considering weights in real social networks: A review

Bellingeri, M.; Bevacqua, D.; Sartori, F. 1; Turchetto, M.; Scotognella, F.; Alfieri, R.; Nguyen, N. K. K.; Le, T. T.; Nguyen, Q.; Cassi, D.
1 Institut für Technikzukünfte (ITZ), Karlsruher Institut für Technologie (KIT)

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.


Verlagsausgabe §
DOI: 10.5445/IR/1000160375
Veröffentlicht am 11.07.2023
Originalveröffentlichung
DOI: 10.3389/fphy.2023.1152243
Scopus
Zitationen: 3
Dimensions
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Technikzukünfte (ITZ)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 2296-424X
KITopen-ID: 1000160375
Erschienen in Frontiers in Physics
Verlag Frontiers Media SA
Band 11
Seiten Art.-Nr.: 1152243
Vorab online veröffentlicht am 28.03.2023
Schlagwörter social networks, weighted networks, weighted network analysis, network science, social physics
Nachgewiesen in Dimensions
Web of Science
Scopus
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