השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ניתוח רשתות חברתיות× | Triad Census× | |
|---|---|---|
| תחום≠ | ניתוח רשתות | Sociology |
| משפחה≠ | Machine learning | Process / pipeline |
| שנת המקור≠ | 1934 (sociometry); 1994 (modern formalization) | 1970 |
| הוגה השיטה≠ | Moreno, J.L.; formalized by Wasserman & Faust | Paul Holland & Samuel Leinhardt |
| סוג≠ | Structural/relational analysis framework | Enumeration of the 16 isomorphism classes of directed triads |
| מקור מכונן≠ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 | Holland, P. W., & Leinhardt, S. (1970). A method for detecting structure in sociometric data. American Journal of Sociology, 76(3), 492–513. DOI ↗ |
| כינויים | SNA, network analysis, sociometric analysis, relational analysis | triad count, triadic census, 16-type triad census, MAN triad census |
| קשורות≠ | 5 | 4 |
| תקציר≠ | 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. | The triad census counts how many of a directed network's three-actor subgroups fall into each of the 16 possible types of triad, providing a compact fingerprint of the network's local structure. Introduced by Paul Holland and Samuel Leinhardt in 1970, it is the standard way to test structural theories — balance, clustering, transitivity, ranked clusters — by comparing the observed distribution of triad types against what a random network would produce. |
| ScholarGateמערך נתונים ↗ |
|
|