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| Multilayer Social Network Analysis× | Analyse sozialer Netzwerke× | |
|---|---|---|
| Fachgebiet | Netzwerkanalyse | Netzwerkanalyse |
| Familie | Machine learning | Machine learning |
| Entstehungsjahr≠ | 2014 | 1934 (sociometry); 1994 (modern formalization) |
| Urheber≠ | Kivela, M.; Boccaletti, S. et al. | Moreno, J.L.; formalized by Wasserman & Faust |
| Typ≠ | Structural network analysis framework | Structural/relational analysis framework |
| Wegweisende Quelle≠ | Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Aliasnamen | MSNA, multiplex network analysis, multilayer network analysis, interconnected network analysis | SNA, network analysis, sociometric analysis, relational analysis |
| Verwandt≠ | 6 | 5 |
| Zusammenfassung≠ | Multilayer social network analysis extends classical single-layer network methods to settings where actors are connected through multiple, distinct types of ties — such as friendship, professional collaboration, and online interaction — simultaneously. By modeling each type of relationship as a separate layer and explicitly representing connections across layers, it captures structural complexity that a single aggregated network would hide. | Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system. |
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