Name
Abstract | ||
|---|---|---|
Social network analysis has been used for quite some time to analyze and understand the behavior of nodes in the network. Theses nodes could be individuals or group of persons, events or organizations etc. Infact these nodes could be any thing importantly, these nodes propagate and obviously have attributes. In this paper a very novel and absolutely new approach to SNA is presented, for locating the important key players in the network. The system also predicts a path comprising of selected nodes which shows the vulnerability of the network and if the path along with these nodes is removed it can reduce/destabilize or even destroy the structure of the network. The paper provides comparative results for a couple of random networks with various numbers of nodes and connections. In addition to these example networks it performs a case study of the nine eleven, 62 node networks (by Valdis E. Krebs) to predict a path for its destabilization. This network is selected to benchmark our proposed model framework. The results obtained with various network analysis shows that it works better than other analysis measures for example based on degree, betweeness and closeness etc. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.4304/jsw.2.6.22-29 | JSW |
Keywords | Field | DocType |
models,intellective simulation model.,terrorism,index terms— social network analysis,simulation model,indexing terms,social network analysis,network analysis | Network formation,Network science,Dynamic network analysis,Interdependent networks,Computer science,Evolving networks,Computer network,Weighted network,Hierarchical network model,Artificial intelligence,Fitness model,Machine learning | Journal |
Volume | Issue | Citations |
2 | 6 | 3 |
PageRank | References | Authors |
0.46 | 0 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dil Muhammad Akbar Hussain | 1 | 48 | 9.16 |