We propose a model of Markovian quantity flows on connected networks that relaxes several properties of the standard compartmental Markov process. The motivation of our generalization are social science applications of the standard model that do not comport with its steady state predictions. The proposed generalization relaxes the predictions that every node belonging to the same nontrivial strong component of a network must acquire the same fraction of its members’ initial quantities and that the sink component(s) of the network must absorb all of the system’s available initial quantity. For example, when applied to refugee flows from a nation in chaos to other nations on a network with one or more sink nations, the standard model predicts that all the refugees will be eventually located in the sink(s) of the network and none that will permanently locate themselves in the nations along the paths to the sink(s). We illustrate this and several other social science applications to which our proposed model is applicable.
Generalized Markovian Quantity Distribution Systems: Social Science Applications / Friedkin, Noah; Proskurnikov, Anton. - In: SOCIOLOGICAL SCIENCE. - ISSN 2330-6696. - ELETTRONICO. - 7(2020), pp. 487-503. [10.15195/v7.a20]
|Titolo:||Generalized Markovian Quantity Distribution Systems: Social Science Applications|
|Data di pubblicazione:||2020|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.15195/v7.a20|
|Appare nelle tipologie:||1.1 Articolo in rivista|