Published June 21, 2013 | Version v1
Journal article

Recruitment dynamics in adaptive social networks

  • 1. Applied Science Department, College of William and Mary, Williamsburg, VA 23187 (United States)
  • 2. Nonlinear Systems Dynamics Section, Plasma Physics Division, Code 6792, US Naval Research Laboratory, Washington, DC 20375 (United States)

Description

We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a susceptible subset of nodes can be recruited. The recruiting individuals may adapt their connections in order to improve recruitment capabilities, thus changing the network structure adaptively. We derive a mean-field theory to predict the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment level, as well as on network topology. The theoretical predictions are compared with direct simulations of the full system. We identify two parameter regimes with qualitatively different bifurcation diagrams depending on whether nodes become susceptible frequently (multiple times in their lifetime) or rarely (much less than once per lifetime). (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1751-8113/46/24/245003

Additional details

Publishing Information

Journal Title
Journal of Physics. A, Mathematical and Theoretical (Online)
Journal Volume
46
Journal Issue
24
Journal Page Range
[15 p.]
ISSN
1751-8121

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
44120396
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Descriptors DEI
BIFURCATION; COMPUTERIZED SIMULATION; DIAGRAMS; MEAN-FIELD THEORY; NETWORK ANALYSIS; TOPOLOGY
Descriptors DEC
INFORMATION; MATHEMATICS; SIMULATION