Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Аналіз модулярності× | Аналіз соціальних мереж× | |
|---|---|---|
| Галузь | Мережевий аналіз | Мережевий аналіз |
| Родина | Machine learning | Machine learning |
| Рік появи≠ | 2004 | 1934 (sociometry); 1994 (modern formalization) |
| Автор методу≠ | Newman, M. E. J. & Girvan, M. | Moreno, J.L.; formalized by Wasserman & Faust |
| Тип≠ | Community detection / graph partitioning | Structural/relational analysis framework |
| Основоположне джерело≠ | Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2), 026113. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Інші назви | Q-modularity, community structure detection, network modularity optimization, graph partitioning by modularity | SNA, network analysis, sociometric analysis, relational analysis |
| Пов'язані | 5 | 5 |
| Підсумок≠ | Modularity analysis is a network science method, formalized by Newman and Girvan in 2004, that detects community structure in graphs by measuring whether edges are more concentrated within groups than expected by chance. Its scalar quality index Q guides algorithms that partition nodes into cohesive clusters, making it the most widely adopted framework for community detection in social, biological, and technological networks. | 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. |
| ScholarGateНабір даних ↗ |
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