Abstract
The key player problem (KPP) identifies a set of key nodes that have a central role in a network. In this paper, we propose a generalized KPP (GKPP) that extends existing work on KPP-Pos and KPP-Neg in such a way that it can consider network structure, node attributes, and the characteristics of edges. We also articulate a novel concept called the key player problem for exclusion (KPP-E), which selects a set of nodes to enforce the centrality of a given set of nodes of interest. To solve this problem efficiently, we propose a sequential greedy algorithm that significantly reduces computational complexity. To corroborate the conceptual meaning and effectiveness of the proposed sequential greedy algorithm, we apply GKPP and KPP-E to several real and random networks.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 24-47 |
| Number of pages | 24 |
| Journal | Computational and Mathematical Organization Theory |
| Volume | 21 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 2015 |
All Science Journal Classification (ASJC) codes
- General Decision Sciences
- General Computer Science
- Modeling and Simulation
- Computational Mathematics
- Applied Mathematics
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