Knopoff, D. On the modeling of migration phenomena on small networks. (English) Zbl 1357.91035 Math. Models Methods Appl. Sci. 23, No. 3, 541-563 (2013). Summary: This paper deals with the modeling of migration phenomena in a small network of nations, with the aim of investigating the influence that the wealth and the welfare policies have on this phenomena. The modeling approach is based on the kinetic theory of active particles, while individuals over the network are distinguished by a scalar variable (the activity) which expresses their social state. The dynamics is induced both by the communication of individuals over the network and by the welfare policy within each nation, which is expressed in terms of competitive and altruistic interactions. The evolution of the discrete probability distribution over the social state is described by a system of nonlinear ordinary differential equations. The existence and uniqueness of the solution is discussed and some specific case-studies are proposed in order to carry out simulations and to investigate the emerging behavior. Cited in 20 Documents MSC: 91D30 Social networks; opinion dynamics 60K35 Interacting random processes; statistical mechanics type models; percolation theory Keywords:kinetic theory; active particles; migration phenomena; population models PDF BibTeX XML Cite \textit{D. Knopoff}, Math. Models Methods Appl. Sci. 23, No. 3, 541--563 (2013; Zbl 1357.91035) Full Text: DOI References: [1] DOI: 10.1016/j.mcm.2009.03.004 · Zbl 1185.91142 [2] DOI: 10.3934/krm.2008.1.249 · Zbl 1141.82357 [3] DOI: 10.1038/nature07950 [4] DOI: 10.1016/j.mcm.2009.12.002 · Zbl 1190.92001 [5] DOI: 10.1142/S0218202512005885 · Zbl 1328.92023 [6] DOI: 10.1016/j.plrev.2010.12.001 [7] DOI: 10.1137/090746677 · Zbl 1231.90123 [8] DOI: 10.1142/S0218202511400069 · Zbl 1242.92065 [9] DOI: 10.1142/S0218202511400033 · Zbl 1243.35157 [10] DOI: 10.1142/S0218202505000923 · Zbl 1093.82016 [11] DOI: 10.1142/S0218202504003544 · Zbl 1083.92032 [12] DOI: 10.1016/j.nonrwa.2006.09.012 · Zbl 1132.91600 [13] DOI: 10.1142/S0218202509003838 · Zbl 1175.92035 [14] DOI: 10.1142/S0218202511005398 · Zbl 1238.92031 [15] DOI: 10.1016/j.physa.2004.01.009 [16] DOI: 10.1016/j.physa.2003.10.041 [17] Ganguly N., Modeling and Simulation in Science, Engineering and Technology, in: Dynamics on and of Complex Networks. Applications to Biology, Computer Science, and the Social Sciences (2009) [18] Gintis H., Game Theory Evolving (2009) · Zbl 1161.91005 [19] DOI: 10.1016/S1090-5138(02)00157-5 [20] DOI: 10.1007/978-3-642-11546-2 · Zbl 1213.91002 [21] DOI: 10.3934/dcdss.2011.4.193 · Zbl 1207.91053 [22] DOI: 10.1016/j.jtbi.2006.06.027 [23] DOI: 10.1103/PhysRevLett.97.258103 [24] DOI: 10.1073/pnas.1108243108 [25] DOI: 10.1142/S0218202511400045 · Zbl 1318.91150 [26] Schweitzer F., Springer Series in Synergetics, in: Brownian Agents and Active Particles: Collective Dynamics in the Natural and Social Sciences (2003) · Zbl 1140.91012 [27] DOI: 10.1142/S0218202508003029 · Zbl 1180.35530 [28] DOI: 10.1142/S0218202511400021 · Zbl 1252.35056 [29] Webb G. F., Monographs and Textbooks in Pure and Applied Mathematics 89, in: Theory of Nonlinear Age-Dependent Population Dynamics (1985) This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.