TY - GEN
T1 - Awareness-Constrained Discrete Choice in Multilayer Network Formation and Evolution
AU - Spencer, Sam
AU - Varshney, Lav R.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - We introduce a generative model for multilayer networks consisting of awareness layers and active layers. Nodes themselves seek to build (or weight) links in active layers based on information available through their connections in awareness layers, including via discrete choice processes. For the generative network models we define, we use actor-based simulations and analytical approaches to examine the properties of resultant networks, such as degree distributions.
AB - We introduce a generative model for multilayer networks consisting of awareness layers and active layers. Nodes themselves seek to build (or weight) links in active layers based on information available through their connections in awareness layers, including via discrete choice processes. For the generative network models we define, we use actor-based simulations and analytical approaches to examine the properties of resultant networks, such as degree distributions.
UR - http://www.scopus.com/inward/record.url?scp=85150212311&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85150212311&partnerID=8YFLogxK
U2 - 10.1109/IEEECONF56349.2022.10052075
DO - 10.1109/IEEECONF56349.2022.10052075
M3 - Conference contribution
AN - SCOPUS:85150212311
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1269
EP - 1275
BT - 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
A2 - Matthews, Michael B.
PB - IEEE Computer Society
T2 - 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
Y2 - 31 October 2022 through 2 November 2022
ER -