This 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.

In an associated paper which focuses on analyzing the structure of several egocentric networks of collective awareness platforms for sustainable innovation (CAPS), this model is developed. It answers the question whether the network structure is determinative for the sustainability of the created awareness. Based on a thorough literature review a model is developed to explain and operationalize the concept of sustainability of a social network in terms of importance, effectiveness and robustness. By developing this agent-based model, the expected outcomes after the dissolution of the CAPS are predicted and compared with the results of a network with the same participants but with different ties. Twitter data from different CAPS is collected and used to feed the simulation. The results show that the structure of the network is of key importance for its sustainability. With this knowledge and the ability to simulate the results after network changes have taken place, CAPS can assess the sustainability of their legacy and actively steer towards a longer lasting potential for social innovation. The retrieved knowledge urges organizations like the European Commission to adopt a more blended approach focusing not only on solving societal issues but on building a community to sustain the initiated development.

The 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.

We study the impact of endogenous creation and destruction of social ties in an artificial society on aggregate outcomes such as generalized trust, willingness to cooperate, social utility and economic performance. To this end we put forward a computational multi-agent model where agents of overlapping generations interact in a dynamically evolving social network. In the model, four distinct dimensions of individuals’ social capital: degree, centrality, heterophilous and homophilous interactions, determine their generalized trust and willingness to cooperate, altogether helping them achieve certain levels of social utility (i.e., utility from social contacts) and economic performance. We find that the stationary state of the simulated social network exhibits realistic small-world topology. We also observe that societies whose social networks are relatively frequently reconfigured, display relatively higher generalized trust, willingness to cooperate, and economic performance – at the cost of lower social utility. Similar outcomes are found for societies where social tie dissolution is relatively weakly linked to family closeness.

This is code repository for the paper “Homophily as a process generating social networks: insights from Social Distance Attachment model”.
It provides all information, code and data necessary to replicate all the simulations and analyses presented in the paper.
This document contains the overall instruction as well as description of the content of the repository.
Details regarding particular stages are documented within source files as comments.

This model is an extended version of the original MERCURY model (https://www.comses.net/codebases/4347/releases/1.1.0/ ) . It allows for experiments to be performed in which empirically informed population sizes of sites are included, that allow for the scaling of the number of tableware traders with the population of settlements, and for hypothesised production centres of four tablewares to be used in experiments.

Experiments performed with this population extension and substantive interpretations derived from them are published in:

Hanson, J.W. & T. Brughmans. In press. Settlement scale and economic networks in the Roman Empire, in T. Brughmans & A.I. Wilson (ed.) Simulating Roman Economies. Theories, Methods and Computational Models. Oxford: Oxford University Press.

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Agents are linked in a social-network and make decisions on which of 2 types of behavior to adopt. We explore consequences of different information feedback and providing targeted feedback to individuals.

The CONSERVAT model evaluates the effect of social influence among farmers in the Lake Naivasha basin (Kenya) on the spatiotemporal diffusion pattern of soil conservation effort levels and the resulting reduction in lake sedimentation.

The Labour Markets and Ethnic Segmentation (LaMESt) Model is a model of a simplified labour market, where only jobs of the lowest skill level are considered. Immigrants of two different ethnicities (“Latino”, “Asian”) compete with a majority (“White”) and minority (“Black”) native population for these jobs. The model’s purpose is to investigate the effect of ethnically homogeneous social networks on the emergence of ethnic segmentation in such a labour market. It is inspired by Waldinger & Lichter’s study of immigration and the social organisation of labour in 1990’s Los Angeles.

We expose RA agent-based model of the opinion and tolerance dynamics in artificial societies. The formal mathematical model is based on the ideas of Social Influence, Social Judgment, and Social Identity theories.