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 7 of 7 results scale-free network clear search
Influence mining framework for complex networks using igraph
Owais Hussain | Published Monday, September 25, 2023IMine is a flexible framework which can be adopt multiple criteria for convergence to solve Influence Minig problems. It can use any diffusion model, as well as resilience to compute the influence of a set of nodes base on the use case.
The code is written and tested on ‘R’ v3.5
Anxiety-to-Approach Agent-Based Model (Netlogo)
Marie Lisa Kogler | Published Tuesday, April 04, 2023An Agent-Based Model to simulate agent reactions to threatening information based on the anxiety-to-approach framework of Jonas et al. (2014).
The model showcases the framework of BIS/BAS (inhibitory and approach motivated behavior) for the case of climate information, including parameters for anxiety, environmental awareness, climate scepticism and pro-environmental behavior intention.
Agents receive external information according to threat-level and information frequency. The population dynamic is based on the learning from that information as well as social contagion mechanisms through a scale-free network topology.
The model uses Netlogo 6.2 and the network extension.
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Exploring the Effects of Link Recommendations on Social Networks
Andrew Crooks Ciara Sibley | Published Thursday, March 19, 2020The purpose of this model is explore how “friend-of-friend” link recommendations, which are commonly used on social networking sites, impact online social network structure. Specifically, this model generates online social networks, by connecting individuals based upon varying proportions of a) connections from the real world and b) link recommendations. Links formed by recommendation mimic mutual connection, or friend-of-friend algorithms. Generated networks can then be analyzed, by the included scripts, to assess the influence that different proportions of link recommendations have on network properties, specifically: clustering, modularity, path length, eccentricity, diameter, and degree distribution.
From Cyber Space Opinion Leaders and the Spread of Anti-Vaccine Extremism to Physical Space Disease Outbreaks
Xiaoyi Yuan | Published Wednesday, March 08, 2017 | Last modified Friday, March 31, 2017This model simulates the spread of anti-vaccine sentiments in cyber and physical space and how it creates emergence of clusters of anti-vacciners, which eventually lead to higher probablity of disease outbreaks.
An Agent-based Model of Collective Self-organisation in Irrigation Management
Hang Xiong Jingjing Cai | Published Wednesday, April 06, 2016This model simulates how collective self-organisation among individuals that manage irrigation resource collectively.
Relative Agreement Model and Network Structure
Spiro Maroulis David Adelberg | Published Friday, January 29, 2016This adaptation of the Relative Agreement model of opinion dynamics (Deffuant et al. 2002) extends the Meadows and Cliff (2012) implementation of this model in a manner that explores the effect of the network structure among the agents.
Chiefdoms and Structural Resilience to Stress
Wendy Cegielski | Published Monday, December 13, 2010 | Last modified Saturday, April 27, 2013Original model of chiefdom modeled in terms of a hierarchical, scale-free network