Name
Abstract | ||
|---|---|---|
Applying the concept of triadic closure to coauthorship networks means that scholars are likely to publish a joint paper if they have previously coauthored with the same people. Prior research has identified moderate to high (20 to 40%) closure rates; suggesting this mechanism is a reasonable explanation for tie formation between future coauthors. We show how calculating triadic closure based on prior operationalizations of closure, namely Newman’s measure for one-mode networks (NCC) and Opsahl’s measure for two-mode networks (OCC) may lead to higher amounts of closure compared to measuring closure over time via a metric that we introduce and test in this paper. Based on empirical experiments using four large-scale, longitudinal datasets, we find a lower bound of 1–3% closure rates and an upper bound of 4–7%. These results motivate research on new explanatory factors for the formation of coauthorship links. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s13278-017-0428-3 | Social Netw. Analys. Mining |
Keywords | Field | DocType |
Clustering coefficient,Transitivity,Triadic closure,Coauthorship networks | Publication,Upper and lower bounds,Triadic closure,Theoretical computer science,Artificial intelligence,Clustering coefficient,Mathematics,Transitive relation | Journal |
Volume | Issue | ISSN |
7 | 1 | Social Network Analysis and Mining, 7(1), 1-12 (2017) |
Citations | PageRank | References |
4 | 0.38 | 11 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinseok Kim | 1 | 51 | 6.74 |
| Jana Diesner | 2 | 216 | 24.38 |