FCMiner
Mining functional communities in social networks
Bibliographic Data
| ID | 16858654 |
|---|---|
| Authors | T M G Tennakoon (0000-0002-7819-1332, Queensland University of Technology, corresponding author), Richi Nayak (0000-0002-9954-0159, Queensland University of Technology) |
| Year | 2019 |
| Volume | 9 |
| Issue | 1 |
| Publication date | 2019-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-019-0565-y |
| OpenAlex | W2947172528 |
| Language | EN |
| References cited | 19 |
Data science · Advanced Clustering Algorithms Research · Complex Network Analysis Techniques · Computer Science · Peer-to-Peer Network Technologies
Maps of random walks on complex networks reveal community structure
Benchmark graphs for testing community detection algorithms
Community detection in networks
Measuring User Influence in Twitter
Computing Communities in Large Networks Using Random Walks
Finding community structure in very large networks
Fast unfolding of communities in large networks
| Highly cited | No |
|---|