Name
Abstract | ||
|---|---|---|
We quantify a social organization's potentiality, that is, its ability to attain different configurations. The organization is represented as a network in which nodes correspond to individuals and (multi-)edges to their multiple interactions. Attainable configurations are treated as realizations from a network ensemble. To have the ability to encode interaction preferences, we choose the generalized hypergeometric ensemble of random graphs, which is described by a closed-form probability distribution. From this distribution we calculate Shannon entropy as a measure of potentiality. This allows us to compare different organizations as well as different stages in the development of a given organization. The feasibility of the approach is demonstrated using data from three empirical and two synthetic systems. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/e21090901 | ENTROPY |
Keywords | Field | DocType |
multi-edge network,network ensemble,Shannon entropy,social organization | ENCODE,Hypergeometric distribution,Combinatorics,Random graph,Social organization,Theoretical computer science,Probability distribution,Entropy (information theory),Mathematics | Journal |
Volume | Issue | Citations |
21 | 9 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Zingg | 1 | 0 | 0.34 |
| Giona Casiraghi | 2 | 0 | 1.01 |
| Giacomo Vaccario | 3 | 9 | 1.81 |
| Frank Schweitzer | 4 | 36 | 4.96 |