About the CoMSES Model Library more info
Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.
All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model publishing tutorial and feel free to contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
We also maintain a curated database of over 7500 publications of agent-based and individual based models with detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
Displaying 5 of 5 results diffusion of information clear search
COMM-PDND: Communication-Based Model of Perceived Descriptive Norm Dynamics in Digital Networks
Lars Reinelt | Published Friday, September 08, 2023The Communication-Based Model of Perceived Descriptive Norm Dynamics in Digital Networks (COMM-PDND) is an agent-based model specifically created to examine the dynamics of perceived descriptive norms in the context of digital network structures. The model, developed as part of a master’s thesis titled “The Dynamics of Perceived Descriptive Norms in Digital Network Publics: An Agent-Based Simulation,” emphasizes the critical role of communication processes in norm formation. It focuses on the role of communicative interactions in shaping perceived descriptive norms.
The COMM-PDND is tuned to explore the effects of normative deviance in digital social networks. It provides functionalities for manipulating agents according to their network position, and has a versatile set of customizable parameters, making it adaptable to a wide range of research contexts.
Peer reviewed Routes & Rumours 0.1.1
Jakub Bijak Martin Hinsch Oliver Reinhardt | Published Tuesday, July 12, 2022Routes & Rumours is an agent-based model of (forced) human migration. We model the formation of migration routes under the assumption that migrants have limited geographical knowledge concerning the transit area and rely to a large degree on information obtained from other migrants.
Seeding for information transmission in social networks
Beatrice Nöldeke Ulrike Grote Etti Winter | Published Tuesday, November 03, 2020This model simulates different seeding strategies for information diffusion in a social network adjusted to a case study area in rural Zambia. It systematically evaluates different criteria for seed selection (centrality measures and hierarchy), number of seeds, and interaction effects between seed selection criteria and set size.
Communication and social change in space and time
Sebastian Kluesener Francesco Scalone Martin Dribe | Published Tuesday, May 17, 2016 | Last modified Friday, October 13, 2017This agent-based model simulates the diffusion of a social change process stratified by social class in space and time which is solely driven social and spatial variation in communication links.
Linear Threshold
Kaushik Sarkar | Published Saturday, November 03, 2012 | Last modified Saturday, April 27, 2013NetLogo implementation of Linear Threshold model of influence propagation.