Name
Abstract | ||
|---|---|---|
Social network analysis is an important research area for supporting intelligence analysts since it can be used to identify important actors and subgroups in e.g. criminal networks. In this paper, we apply methods from social network analysis on bibliographic data about the research area of information fusion, in order to demonstrate how this kind of algorithms can be applied to get a better overview of the information fusion research community. The results show which authors have published the most in the research community, which authors that are most “powerful” in terms of various metrics widely used in social network analysis, and what the most and least active geographical areas are. |
Year | Venue | Keywords |
|---|---|---|
2011 | Information Fusion | bibliographic systems,data acquisition,sensor fusion,social networking (online),bibliographic data,criminal networks,geographical areas,information fusion community,information fusion research community,intelligence analysts,social network analysis,Information fusion,Intelligence analysis,SNA,Social network analysis |
Field | DocType | ISBN |
Data science,Level measurement,Computer science,Social network analysis,Sensor fusion,Tag cloud,Bibliometrics,Information fusion,Intelligence analysis | Conference | 978-1-4577-0267-9 |
Citations | PageRank | References |
1 | 0.36 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fredrik Johansson | 1 | 95 | 7.18 |
| Christian Martenson | 2 | 55 | 3.93 |
| Pontus Svenson | 3 | 149 | 22.31 |