A comprehensive comparison of graph theory metrics for social networks
Bibliographic Data
| ID | 4657732 |
|---|---|
| Authors | Bryan Ek (0000-0002-7279-2188, Rochester Institute of Technology), Caitlin Verschneider (Nazareth College), Nathan D Cahill (0000-0002-6164-3291, Rochester Institute of Technology), Darren A Narayan (Rochester Institute of Technology, corresponding author) |
| Year | 2015 |
| Volume | 5 |
| Issue | 1 |
| Publication date | 2015-12-01 |
| 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/s13278-015-0272-2 |
| OpenAlex | W2208130621 |
| Language | EN |
| Citations received | 1 |
| References cited | 12 |
Cluster analysis · Clustering coefficient · Combinatorics · Data mining · Graph · Graph theory · Machine learning · Social media · World Wide Web · Bioinformatics and Genomic Networks · Complex Network Analysis Techniques · Computer Science · Functional Brain Connectivity Studies · Mathematics · Artificial Intelligence · Theoretical Computer Science
Identifying sets of key players in a social network
Benchmark graphs for testing community detection algorithms
Efficient Behavior of Small-World Networks
Collective dynamics of ‘small-world’ networks
Community structure in social and biological networks
Centrality in social networks conceptual clarification
Clustering and Structural Balance in Graphs
| Citations per year | 0.13 |
|---|---|
| Citation span | 2018 - 2018 (1) |
| Highly cited | No |