ScholarGate
Asisten

Bandingkan metode

Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.

PageRank Berbobot×Analisis Jaringan Sosial×
BidangAnalisis JaringanAnalisis Jaringan
KeluargaMachine learningMachine learning
Tahun asal20041934 (sociometry); 1994 (modern formalization)
PencetusXing, W. & Ghorbani, A.Moreno, J.L.; formalized by Wasserman & Faust
TipeCentrality measure / ranking algorithmStructural/relational analysis framework
Sumber perintisXing, W., & Ghorbani, A. (2004). Weighted PageRank algorithm. Proceedings of the Second Annual Conference on Communication Networks and Services Research (CNSR '04), pp. 305–314. IEEE. DOI ↗Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1
AliasWPR, weighted page rank, edge-weighted PageRank, strength-based PageRankSNA, network analysis, sociometric analysis, relational analysis
Terkait65
RingkasanWeighted PageRank extends the classic PageRank algorithm to networks where edges carry different strengths or frequencies, distributing importance proportionally to both incoming and outgoing edge weights rather than treating all links equally. This makes it substantially more informative than binary PageRank in any network where connection strength matters.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.
ScholarGateSet data
  1. v1
  2. 2 Sumber
  3. PUBLISHED
  1. v1
  2. 2 Sumber
  3. PUBLISHED

Ke halaman pencarian Unduh salindia

ScholarGateBandingkan metode: Weighted PageRank · Social Network Analysis. Diakses 2026-06-18 dari https://scholargate.app/id/compare