Karmeshu Karmeshu
Biographic Data
| ID | 5151386 |
|---|---|
| NAME | Karmeshu Karmeshu |
| GIVEN NAMES | Karmeshu |
| FAMILY NAME | Karmeshu |
| SIGNATURE | KARMESHU K |
| AFFILIATIONS | University of Waterloo |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 25 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1980 |
| LATEST PUBLICATION YEAR | 1983 |
| H-INDEX | 3 |
Diffusion of information in a social group
A generalized model of diffusion of information in a closed, homogeneously mixing population of size N is considered. Apart from the provision of mass‐mediated and interactively mediated messages and the possibility of spontaneous loss of interest, the model allows for the possibility of the process being stifled by a section of the people who possess the information but do not propagate it; they rather hinder the process by “turning off” the spr…
Diffusion of information in a random environment
The effects of random environmental fluctuations on the process of diffusion of information in a social group are investigated. The methodology of this investigation is based on a study of “stochastic differential equations with fluctuating parameters,” under the assumption that the time scale of the fluctuations in the various parameters is much shorter than that of the macroscopic variables of the system. This enables us to convert a stochastic…
Time development of a Markov process in a finite population
A systematic procedure of truncating the hierarchy of moment equations describing the stochastic evolution of a Markov process in a finite population is developed. The procedure makes use of the asymptotic expression for a certain higher‐order moment of the relevant probability distribution and yields finite‐size corrections to all lower‐order moments. The usefulness of the method is illustrated by applying it to study the mean and the variance o…
Stochastic evolution of a nonlinear model of diffusion of information
A theoretical method based on the concept of “system‐sized expansion” is applied to a generalization of Bartholomew's model of diffusion of information in a population of size N. The model considers a combination of mass‐mediated and interactively mediated messages, with the provision that the spreaders of information may not remain active for an indefinite period of time; it also takes into account the possibility that the parameters governing t…
Stochastic evolution of competing social groups
A model is considered for a situation in which two social groups compete with each other, ultimately resulting in the possible suppression of one of the groups. Using the method of system‐size expansion, an asymptotic analysis of the model, including the time evolution of both deterministic and stochastic aspects of the process, is carried out. The probability distribution of the maximum size attained by the weaker group, just before the commence…
Stochastic evolution of a nonlinear model of diffusion of information
A theoretical method based on the concept of “system‐sized expansion” is applied to a generalization of Bartholomew's model of diffusion of information in a population of size N. The model considers a combination of mass‐mediated and interactively mediated messages, with the provision that the spreaders of information may not remain active for an indefinite period of time; it also takes into account the possibility that the parameters governing t…
Stochastic evolution of competing social groups
A model is considered for a situation in which two social groups compete with each other, ultimately resulting in the possible suppression of one of the groups. Using the method of system‐size expansion, an asymptotic analysis of the model, including the time evolution of both deterministic and stochastic aspects of the process, is carried out. The probability distribution of the maximum size attained by the weaker group, just before the commence…
Time development of a Markov process in a finite population
A systematic procedure of truncating the hierarchy of moment equations describing the stochastic evolution of a Markov process in a finite population is developed. The procedure makes use of the asymptotic expression for a certain higher‐order moment of the relevant probability distribution and yields finite‐size corrections to all lower‐order moments. The usefulness of the method is illustrated by applying it to study the mean and the variance o…
Diffusion of information in a social group
A generalized model of diffusion of information in a closed, homogeneously mixing population of size N is considered. Apart from the provision of mass‐mediated and interactively mediated messages and the possibility of spontaneous loss of interest, the model allows for the possibility of the process being stifled by a section of the people who possess the information but do not propagate it; they rather hinder the process by “turning off” the spr…
Diffusion of information in a random environment
The effects of random environmental fluctuations on the process of diffusion of information in a social group are investigated. The methodology of this investigation is based on a study of “stochastic differential equations with fluctuating parameters,” under the assumption that the time scale of the fluctuations in the various parameters is much shorter than that of the macroscopic variables of the system. This enables us to convert a stochastic…
Diffusion of information in a random environment
The effects of random environmental fluctuations on the process of diffusion of information in a social group are investigated. The methodology of this investigation is based on a study of “stochastic differential equations with fluctuating parameters,” under the assumption that the time scale of the fluctuations in the various parameters is much shorter than that of the macroscopic variables of the system. This enables us to convert a stochastic…
Time development of a Markov process in a finite population
A systematic procedure of truncating the hierarchy of moment equations describing the stochastic evolution of a Markov process in a finite population is developed. The procedure makes use of the asymptotic expression for a certain higher‐order moment of the relevant probability distribution and yields finite‐size corrections to all lower‐order moments. The usefulness of the method is illustrated by applying it to study the mean and the variance o…
Stochastic evolution of a nonlinear model of diffusion of information
A theoretical method based on the concept of “system‐sized expansion” is applied to a generalization of Bartholomew's model of diffusion of information in a population of size N. The model considers a combination of mass‐mediated and interactively mediated messages, with the provision that the spreaders of information may not remain active for an indefinite period of time; it also takes into account the possibility that the parameters governing t…
Stochastic evolution of competing social groups
A model is considered for a situation in which two social groups compete with each other, ultimately resulting in the possible suppression of one of the groups. Using the method of system‐size expansion, an asymptotic analysis of the model, including the time evolution of both deterministic and stochastic aspects of the process, is carried out. The probability distribution of the maximum size attained by the weaker group, just before the commence…
Diffusion of information in a social group
A generalized model of diffusion of information in a closed, homogeneously mixing population of size N is considered. Apart from the provision of mass‐mediated and interactively mediated messages and the possibility of spontaneous loss of interest, the model allows for the possibility of the process being stifled by a section of the people who possess the information but do not propagate it; they rather hinder the process by “turning off” the spr…
Mathematics (5 works) · Physics (5 works) · Statistics (5 works) · Diffusion (4 works) · Opinion Dynamics and Social Influence (4 works) · Population (4 works) · Statistical physics (4 works) · Applied Mathematics (3 works) · Applied Mathematics (3 works) · Computer Science (3 works)