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Satoru Morita

Publications and source records attributed to Satoru Morita.

16 recordsLinked to original sources
arXiv2026

Cross-country structure of a sexual contact network derived from a commercial-sex review platform

Sexual contact networks are fundamental to understanding the spread of sexually transmitted infections (STIs), yet their large-scale structure remains difficult to observe because of technical, ethical, and privacy constraints. Here, we analyze a large bipartite commercial-sex contact network comprising 1,436,738 client-sex worker links, constructed from reviews posted between 1999 and 2024 on The Erotic Review (TER), a review platform covering sex workers listed across 97 countries and territories. We examine the network's cross-country structure, focusing on how clients, sex workers, locations, and time periods are connected. The network formed a giant connected component containing most clients and sex workers and exhibited small-world-like properties, including short average path lengths, high bipartite clustering, and disassortative degree correlations. Although most reviews were associated with the United States, a small fraction of clients reviewed sex workers in multiple countries or territories, creating spatial bridges between otherwise distant regions. Long-term users created temporal bridges, making the aggregated network more compact than networks built from shorter time windows. Contacts involving transgender female sex workers were structurally concentrated: clients who reviewed both cisgender and transgender female sex workers represented a small minority but accounted for a large share of transgender-related reviews and showed higher cross-country activity. These findings show how a small number of highly connected clients with cross-country review activity can shape the large-scale connectivity of commercial-sex contact networks. More broadly, our results demonstrate the value and limitations of digital trace data for studying cross-country contact structures relevant to STI transmission.

cs.SI↗
arXiv2023

Representation of degree correlation using eigenvalue decomposition and its application to epidemic models

Degree correlation plays a crucial role in studying network structures; however, its varied forms pose challenges to understanding its impact on network dynamics. This study devised a method that uses eigenvalue decomposition to characterize degree correlations. Additionally, the applicability of this method was demonstrated by approximating the basic and type reproduction numbers in an epidemic network model. The findings elucidate the interplay between degree correlations and epidemic behavior, thus contributing to a deeper understanding of complex networks and their dynamics.

physics.soc-ph↗
arXiv2020

Solvable epidemic model on degree-correlated networks

Disease and information spread over social and information networks. Understanding the spread phenomena in networks requires paying attention not only to the degree distribution but also to the degree correlation. However, it is considered difficult to analytically deal with the effect of degree correlation on spread phenomena. Here, we introduce degree correlation using a simple method and present the theoretical formulas of the outbreak threshold and basic reproduction number. We theoretically clarify the effect of the degree correlation.

physics.soc-ph↗
arXiv2020

Type reproduction number for epidemic models on heterogeneous networks

Infection can spread easily on networks with heterogeneous degree distribution. Here, we considered targeted immunization on such networks, wherein a fraction of individuals with the highest connectivity are immunized. To quantify the effect of this targeted immunization approach on population immunity, we proposed a method using the type reproduction number. Consequently, we derived a precise and simple formula that can yield the immunization threshold, which, to the best of our knowledge, is the first such result presented in the literature.

physics.soc-ph↗
arXiv2017

Power-law exponent in multiplicative Langevin equation with temporally correlated noise

Power-law distributions are ubiquitous in nature. Random multiplicative processes are a basic model for the generation of power-law distributions. It is known that, for discrete-time systems, the power-law exponent decreases as the autocorrelation time of the multiplier increases. However, for continuous-time ystems, it has not yet been elucidated as to how the temporal correlation affects the power-law behavior. Herein, we have analytically investigated a multiplicative Langevin equation with colored noise. We show that the power-law exponent depends on the details of the multiplicative noise, in contrast to the case of discrete-time systems.

cond-mat.stat-mech↗
arXiv2015

Power law in random multiplicative processes with spatio-temporal correlated multipliers

It is well known that random multiplicative processes generate power-law probability distributions. We study how the spatio-temporal correlation of the multipliers influences the power-law exponent. We investigate two sources of the time correlation: the local environment and the global environment. In addition, we introduce two simple models through which we analytically and numerically show that the local and global environments yield different trends in the power-law exponent.

nlin.AO↗
arXiv2015

Six Susceptible-Infected-Susceptible Models on Scale-free Networks

Spreading phenomena are ubiquitous in nature and society. For example, disease, rumor, and information spread over underlying social and information networks. It is well known that there is no threshold for epidemic models on scale-free networks; this suggests that disease can spread on such networks, regardless of how low the contact rate may be. In this paper, I consider six models with different contact and propagation mechanisms. Each model is analyzed by degree-based mean-field theory. I show that the presence or absence of an outbreak threshold depends on the contact and propagation mechanism.

physics.soc-ph↗
arXiv2015

Evolutionary game on networks with high clustering coefficient

This study investigates the influence of lattice structure in evolutionary games. The snowdrift games is considered in networks with high clustering coefficients, that use four different strategy-updating. Analytical conjectures using pair approximation were compared with the numerical results. Results indicate that general statements asserting that the lattice structure enhances cooperation are misleading.

q-bio.PE↗
arXiv2014

Disadvantages of Preferential Dispersals in Fluctuating Environments

It has not been known whether preferential dispersal is adaptive in fluctuating environments. We investigate the effect of preferential and random dispersals in bet-hedging systems by using a discrete stochastic metapopulation model, where each site fluctuates between good and bad environments with temporal correlation. To explore the optimal migration pattern, an analytical estimation of the total growth is derived by mean field approximation. We found that the preference for fertile sites is disadvantageous when transportation among sites has a cost or the sensitivity of preference is high.

q-bio.PE↗
arXiv2013

Analytical solution of stochastic model of risk-spreading with global coupling

We study a stochastic matrix model to understand the mechanics of risk-spreading (or bet-hedging) by dispersion. Such model has been mostly dealt numerically except for well-mixed case, so far. Here, we present an analytical result, which shows that optimal dispersion leads to Zipf's law. Moreover, we found that the arithmetic ensemble average of the total growth rate converges to the geometric one, because the sample size is finite.

physics.soc-ph↗
arXiv2012

Analytical Solution of Metapopulation Dynamics in Stochastic Environment

We study a stochastic linear discrete metapolulation model to understand the effect of risk spreading by dispersion. We calculate analytically the stable distribution of populations that live in different habitats. The result shows that the simultaneous distribution of the populations has a complicated self-similar structure, but a population at each habitat follows a log-normal distribution.

q-bio.PE↗
arXiv2008

Population Uncertainty in Model Ecosystem: Analysis by Stochastic Differential Equation

Perturbation experiments are carried out by contact process and its mean-field version. Here, the mortality rate is increased or decreased suddenly. It is known that the fluctuation enhancement (FE) occurs after the perturbation, where FE means a population uncertainty. In the present paper, we develop a new theory of stochastic differential equation. The agreement between the theory and the mean-field simulation is almost perfect. This theory enables us to find much stronger FE than reported previously. We discuss the population uncertainty in the recovering process of endangered species.

q-bio.PE↗
arXiv2008

Extended Pair Approximation of Evolutionary Game on Complex Networks

We investigate how network structure influences evolutionary games on networks. We extend the pair approximation to study the effects of degree fluctuation and clustering of the network. We find that a larger fluctuation of the degree is equivalent to a larger mobility of the players. In addition, a larger clustering coefficient is equivalent to a smaller number of neighbors.

physics.soc-ph↗
arXiv2005

Crossovers in ScaleFree Networks on Geographical Space

Complex networks are characterized by several topological properties: degree distribution, clustering coefficient, average shortest path length, etc. Using a simple model to generate scale-free networks embedded on geographical space, we analyze the relationship between topological properties of the network and attributes (fitness and location) of the vertices in the network. We find there are two crossovers for varying the scaling exponent of the fitness distribution.

cond-mat.dis-nn↗
arXiv1995

Bifurcations in Globally Coupled Chaotic Maps

We propose a new method to investigate collective behavior in a network of globally coupled chaotic elements generated by a tent map. In the limit of large system size, the dynamics is described with the nonlinear Frobenius-Perron equation. This equation can be transformed into a simple form by making use of the piecewise linear nature of the individual map. Our method is applied successfully to the analyses of stability of collective stationary states and their bifurcations.

chao-dyn↗