Myong‐Hun Chang
Biographic Data
| ID | 5000405 |
|---|---|
| NAME | Myong‐Hun Chang |
| GIVEN NAMES | Myong‐Hun |
| FAMILY NAME | Chang |
| SIGNATURE | CHANG M H |
| AFFILIATIONS | Cleveland State University |
| ORCID | 0000-0002-2023-9778 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 4 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2005 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Spatial Disparities in Vaccination and the Risk of Infection in a Multi-Region Agent-Based Model of Epidemic Dynamics
We investigate the impact that disparities in regional vaccine coverage have on the risk of infection for an unvaccinated individual. To address this issue, we develop an agent-based computational model of epidemics with two features: 1) a population divided among multiple regions with heterogeneous vaccine coverage; 2) contact networks for individuals that allow for both intra-regional interactions and inter-regional interactions. The benchmark …
A Dynamic Computational Model of Social Stigma
The dynamics of social stigma are explored in the context of di usion models. Our focus is on exploring the dynamic process through which the behavior of individuals and the interpersonal relationships among them influence the macro-social attitude towards the stigma. We find that a norm of tolerance is best promoted when the population comprises both those whose conduct is driven by compassion for the stigmatized and those whose focus is on conf…
Discovery and Diffusion of Knowledge in an Endogenous Social Network
The authors explore the evolution of the structure and performance of a social network in a population of individuals who search for local optima in diverse and dynamic environments. Individuals choose whether to innovate or imitate, and in the latter case, from whom to learn. The probabilities of these possible actions respond to an individual’s past experiences using reinforcement learning. Among some of the authors’ more interesting findings i…
Discovery and Diffusion of Knowledge in an Endogenous Social Network
The authors explore the evolution of the structure and performance of a social network in a population of individuals who search for local optima in diverse and dynamic environments. Individuals choose whether to innovate or imitate, and in the latter case, from whom to learn. The probabilities of these possible actions respond to an individual’s past experiences using reinforcement learning. Among some of the authors’ more interesting findings i…
Discovery and Diffusion of Knowledge in an Endogenous Social Network
The authors explore the evolution of the structure and performance of a social network in a population of individuals who search for local optima in diverse and dynamic environments. Individuals choose whether to innovate or imitate, and in the latter case, from whom to learn. The probabilities of these possible actions respond to an individual’s past experiences using reinforcement learning. Among some of the authors’ more interesting findings i…
A Dynamic Computational Model of Social Stigma
The dynamics of social stigma are explored in the context of di usion models. Our focus is on exploring the dynamic process through which the behavior of individuals and the interpersonal relationships among them influence the macro-social attitude towards the stigma. We find that a norm of tolerance is best promoted when the population comprises both those whose conduct is driven by compassion for the stigmatized and those whose focus is on conf…
Spatial Disparities in Vaccination and the Risk of Infection in a Multi-Region Agent-Based Model of Epidemic Dynamics
We investigate the impact that disparities in regional vaccine coverage have on the risk of infection for an unvaccinated individual. To address this issue, we develop an agent-based computational model of epidemics with two features: 1) a population divided among multiple regions with heterogeneous vaccine coverage; 2) contact networks for individuals that allow for both intra-regional interactions and inter-regional interactions. The benchmark …
Psychology (3 works) · Computer Science (2 works) · Demography (2 works) · Population (2 works) · Sociology (2 works) · Artificial Intelligence (1 works) · Artificial Intelligence (1 works) · Cognitive psychology (1 works) · COVID-19 epidemiological studies (1 works) · Demography (1 works)