arXiv subjects

Gholamreza Jafari

Publications and source records attributed to Gholamreza Jafari.

6 recordsLinked to original sources

arXiv2023

Response of the competitive balance model to the external field

The competitive balance model was proposed as an extension of the structural balance theory, aiming to account for heterogeneities observed in real-world networks. In this model, different paradigms lead to form different friendship and enmity. As an example, friendship or enmity between countries can have a political or religious basis. The suggested Hamiltonian is symmetrical between paradigms. Our analyses show that a balanced state can be achieved if just one paradigm prevails in the network and the paradigm shift is possible only by imposing an external field. In this paper, we investigate the influence of the external field on the evolution of the network. We drive the mean-field solutions of the model and verify the accuracy of our analytical solutions by performing Monte-Carlo simulations. We observe that the external field breaks the symmetry of the system. The response of the system to this external field, contingent upon temperature, can be either paramagnetic or ferromagnetic. We observed a hysteresis behavior in the ferromagnetic regime. Once communities are formed based on a certain paradigm, then they resist change. We found that to avoid wasting energy we need to know the level of stochastic behavior in the network. Analogous to magnetic systems, we observe that susceptibility adheres to Curie's law.

physics.soc-ph↗

arXiv2020

The strategy of survival for a competition between normal and anomalous diffusion

In this paper, we study the competition of two diffusion processes for achieving the maximum possible diffusion in an area. This competition, however, does not occur in the same circumstance; one of these processes is a normal diffusion with a higher growth rate, and another one is an anomalous diffusion with a lower growth rate. The trivial solution of the proposed model suggests that the winner is the one with the higher growth rate. But, the question is: what characteristics and strategies should the second diffusion include to prolong the survival in such a competition? The studied diffusion equations correspond to the SI model such that the anomalous diffusion has memory described by a fractional order derivative. The strategy promise that anomalous diffusion reaches maximum survival in case of forgetting some parts of the memory. This model can represent some of real phenomena, such as the contest of two companies in a market share, the spreading of two epidemic diseases, the diffusion of two species, or any reaction-diffusion related to real-world competition.

physics.soc-ph↗

arXiv2019

Optimization of the post-crisis recovery plans in scale-free networks

General Motors or a local business, which one is better to be stimulated in post-crisis recessions, where government stimulation is meant to overcome recessions? Due to the budget constraints, it is quite relevant to ask how one can increase the chance of economic recovery. One of the key elements to answer this question is to understand metastable features of the economic networks. Ising model has been suggested for studying such features in the literature. In the homogenous networks one needs at least a minimum activation, forcing an Ising network to switch its local equilibria, where such minimum is independent of the nodes characteristics. In the scale free networks however, when one aims to push the network to switch its vacuum, she faces the question of which nodes are better to be stimulated to minimize the cost. In the paper it has been shown that stimulation of the high degree nodes costs less in general. Despite regular networks, in the scale free networks, the stimulation cost depends on the networks features such as assortativity. Though we have utilized the Ising model to tackle a problem in economics, our analysis shed lights on many other problems concerning stimulations of socio-economic systems.

physics.soc-ph↗

arXiv2017

Fractional Dynamics of Network Growth Constrained by aging Node Interactions

In many social complex systems, in which agents are linked by non-linear interactions, the history of events strongly influences the whole network dynamics. However, a class of "commonly accepted beliefs" seems rarely studied. In this paper, we examine how the growth process of a (social) network is influenced by past circumstances. In order to tackle this cause, we simply modify the well known preferential attachment mechanism by imposing a time dependent kernel function in the network evolution equation. This approach leads to a fractional order Barabasi-Albert (BA) differential equation, generalizing the BA model. Our results show that, with passing time, an aging process is observed for the network dynamics. The aging process leads to a decay for the node degree values, thereby creating an opposing process to the preferential attachment mechanism. On one hand, based on the preferential attachment mechanism, nodes with a high degree are more likely to absorb links; but, on the other hand, a node's age has a reduced chance for new connections. This competitive scenario allows an increased chance for younger members to become a hub. Simulations of such a network growth with aging constraint confirm the results found from solving the fractional BA equation. We also report, as an exemplary application, an investigation of the collaboration network between Hollywood movie actors. It is undubiously shown that a decay in the dynamics of their collaboration rate is found, - even including a sex difference. Such findings suggest a widely universal application of the so generalized BA model.

physics.soc-ph↗

arXiv2015

History effects on network growth

Growth dynamic of real networks because of emerging complexities is an open and interesting question. Indeed it is not realistic to ignore history impact on the current events. The mystery behind that complexity could be in the role of history in some how. To regard this point, the average effect of history has been included by a kernel function in differential equation of Barabasi Albert (BA) model . This approach leads to a fractional order BA differential equation as a generalization of BA model. As opposed to unlimited growth for degree of nodes, our results show that over time the memory impact will cause a decay for degrees. This gives a higher chance to younger members for turning to a hub. In fact in a real network, there are two competitive processes. On one hand, based on preferential attachment mechanism nodes with higher degree are more likely to absorb links. On the other hand, node history through aging process prevents new connections. Our findings from simulating a network grown by considering these effects also from studying a real network of collaboration between Hollywood movie actors conforms the results and significant effects of history and time on dynamic.

physics.soc-ph↗

arXiv2013

Coupling between time series: a network view

Recently, the visibility graph has been introduced as a novel view for analyzing time series, which maps it to a complex network. In this paper, we introduce new algorithm of visibility, "cross-visibility", which reveals the conjugation of two coupled time series. The correspondence between the two time series is mapped to a network, "the cross-visibility graph", to demonstrate the correlation between them. We applied the algorithm to several correlated and uncorrelated time series, generated by the linear stationary ARFIMA process. The results demonstrate that the cross-visibility graph associated with correlated time series with power-law auto-correlation is scale-free. If the time series are uncorrelated, the degree distribution of their cross-visibility network deviates from power-law. For more clarifying the process, we applied the algorithm to real-world data from the financial trades of two companies, and observed significant small-scale coupling in their dynamics.

physics.data-an↗