Name
Abstract | ||
|---|---|---|
The importance of the betweenness centrality measure in (on-line) social networks is well known, as well as its possible applications to various domains. However, the classical notion of betweenness centrality is not able to capture the centrality of nodes w.r.t. paths crossing different social networks. In other words, it is not able to detect those nodes of a multi-social-network scenario (called Social Internetworking Scenario) which play a central role in inter-social-network information flows. In this paper, we propose a new measure of betweenness centrality suitable for Social Internetworking Scenarios, also applicable to the case of different communities of the same social network. The new measure has been tested in a number of synthetic networks, highlighting the significance and effectiveness of our proposal. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-41033-8_84 | Lecture Notes in Computer Science |
Field | DocType | Volume |
Data science,Network science,Social network,Random walk closeness centrality,Centrality,Betweenness centrality,Artificial intelligence,Network theory,Katz centrality,Mathematical sociology,Mathematics | Conference | 8186 |
ISSN | Citations | PageRank |
0302-9743 | 4 | 0.41 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francesco Buccafurri | 1 | 998 | 95.97 |
| Gianluca Lax | 2 | 358 | 38.52 |
| Serena Nicolazzo | 3 | 49 | 9.57 |
| Antonino Nocera | 4 | 319 | 27.82 |
| Domenico Ursino | 5 | 897 | 104.96 |