Name
Abstract | ||
|---|---|---|
Analyzing social networks enables us to detect several inter and intra connections between people in and outside their organizations. We model a multi-relational scientific social network where researchers may have four different types of relationships with each other. We adopt some criteria to enable the modeling of a scientific social network as close as possible to reality. Using clustering techniques with maximum flow measure, we identify the social structure and research communities in a way that allows us to evaluate the knowledge flow in the Brazilian scientific community. Finally, we evaluate the temporal evolution of scientific social networks to suggest/predict new relationships. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.jss.2013.02.024 | Journal of Systems and Software |
Keywords | Field | DocType |
social structure,social network,brazilian scientific community,link analysis,maximum flow measure,multi-relational scientific social network,intra connection,scientific social network,clustering technique,different type,knowledge flow | Dynamic network analysis,Data science,Social network,Link analysis,Computer science,Maximum flow problem,Cluster analysis,Knowledge flow | Journal |
Volume | Issue | ISSN |
86 | 7 | 0164-1212 |
Citations | PageRank | References |
17 | 0.68 | 33 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Victor StröEle | 1 | 29 | 11.27 |
| Geraldo Zimbrão | 2 | 94 | 15.81 |
| Jano M. Souza | 3 | 41 | 7.25 |