Name
Title | ||
|---|---|---|
Social network analysis of biomedical research collaboration networks in a CTSA institution. |
Abstract | ||
|---|---|---|
•We model research collaborations as a weighted undirected graph.•Research collaboration network is small-world but not scale-free.•The Clinical and Translational Science Award has positive impacts on collaborations.•Combining various centrality measures offers a concise ranking of influential nodes.•Link prediction model can identify potentially successful collaborations. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.jbi.2014.01.015 | Journal of Biomedical Informatics |
Keywords | Field | DocType |
Research collaboration network,Network analysis,Clinical and Translational Science Award (CTSA),Link prediction,Influential node,Small-world | Data science,Clinical and Translational Science Award,Data mining,Network dynamics,Social network,Ranking,Computer science,Social network analysis,Centrality,Weighted network,Network analysis | Journal |
Volume | Issue | ISSN |
52 | C | 1532-0464 |
Citations | PageRank | References |
4 | 0.43 | 11 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiang Bian | 1 | 150 | 43.09 |
| Mengjun Xie | 2 | 212 | 23.46 |
| Umit Topaloglu | 3 | 108 | 10.38 |
| Teresa Hudson | 4 | 4 | 1.11 |
| Hari Eswaran | 5 | 36 | 9.23 |
| William R. Hogan | 6 | 294 | 53.52 |