The model explores the informational causes of polarization and bi-polarization of opinions in groups. To this end it expands the model of the Argument Communication Theory of Bi-polarization. The latter is an argument-based multi-agent model of opinion dynamics inspired by Persuasive Argument Theory. The original model can account for polarization as an outcome of pure informational influence, and reproduces bi-polarization effects by postulating an additional mechanism of homophilous selection of communication partners. The expanded model adds two dimensions: argument strength and more sophisticated protocols of informational influence (argument communication and opinion update).

This version 2.1.0 of the uFunk model is about setting a business strategy (the S in the name) for an organization. A team of managers (or executives) meet and discuss various options on the strategy for the firm. There are three aspects that they have to agree on to set the strategic positioning of the organization.
The discussion is on market, stakeholders, and resources. The team (it could be a business strategy task force) considers various aspects of these three elements. The resources they use to develop the discussion can come from a traditional approach to strategy or from non-traditional means (e.g., so-called serious play, creativity and imagination techniques).
The S-uFunk 2.1.0 Model wants to understand to which extent cognitive means triggered by traditional and non-traditional resources affect the making of the strategy process.

The Social Identity Model of Protest Emergence (SIMPE), an agent-based model of national identity and protest mobilisations.

I developed this model for my PhD project, “Polarisation and Protest Mobilisation Around Secessionist Movements: an Agent-Based Model of Online and Offline Social Networks”, at the University of Glasgow (2019-2023).

The purpose of this model is to simulate protest emergence in a given country where there is an independence movement, fostering the self-categorisation process of national identification. In order to contextualised SIMPE, I have used Catalonia, where an ongoing secessionist movement since 2011 has been present, national identity has shown signs of polarisation, and where numerous mobilisations have taken place over the last decade. Data from the Catalan Centre of Opinion Studies (CEO) has been used to inform some of the model parameters.

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Risk assessments are designed to measure cumulative risk and promotive factors for delinquency and recidivism, and are used by criminal and juvenile justice systems to inform sanctions and interventions. Yet, these risk assessments tend to focus on individual risk and often fail to capture each individual’s environmental risk. This agent-based model (ABM) explores the interaction of individual and environmental risk on the youth. The ABM is based on an interactional theory of delinquency and moves beyond more traditional statistical approaches used to study delinquency that tend to rely on point-in-time measures, and to focus on exploring the dynamics and processes that evolve from interactions between agents (i.e., youths) and their environments. Our ABM simulates a youth’s day, where they spend time in schools, their neighborhoods, and families. The youth has proclivities for engaging in prosocial or antisocial behaviors, and their environments have likelihoods of presenting prosocial or antisocial opportunities.

An agent-based model that simulates urban neighbourhoods. The model has been designed to simulate perceived livability and safety (PLS) of citizens. The score attached to perceived livability and safety, PLS, is the main output of the model and is the average of each individual’s PLS. These PLS scores, in turn, are specific to each citizen and highly dependent on their individual experiences. PLS is impacted by several different social factors: interactions with fellow citizens, police officers, and community workers; visiting or starting a neighbourhood initiative; experiencing a burglary; seeing a youth gang; or hearing from friends (of friends) about these events. On top of this, the model allows to set various types of social networks which also influence the PLS.

This is an interdisciplinary agent-based model with Monte Carlo simulations to assess the relative effects of broadcast and contagion processes in a multiplex social network. This multiplex approach models multiple channels of informal communication - phone, word-of-mouth, and social media - that vary in their attribute values. Each agent is an individual in a threatened community who, once warned, has a probability of warning others in their social network using one of these channels. The probability of an individual warning others is based on their warning source and the time remaining until disaster impact, among other variables. Default parameter values were chosen from empirical studies of disaster warnings along with the spatial aspects of Coos Bay, OR, USA and Seaside, OR, USA communities.

Organizations are complex systems comprised of many dynamic and evolving interaction patterns among individuals and groups. Understanding these interactions and how patterns, such as informal structures and knowledge sharing behavior, emerge are crucial to creating effective and efficient organizations. To explore such organizational dynamics, the agent-based model integrates a cognitive model, dynamic social networks, and a physical environment.

This is an original model of (sub)culture diffusion.
It features a set of agents (dubbed “partygoers”) organized initially in clusters, having properties such as age and a chromosome of opinions about 6 different topics. The partygoers interact with a set of cultures (also having a set of opinions subsuming those of its members), in the sense of refractory or unhappy members of each setting about to find a new culture and trading information encoded in the genetic string (originally encoded as -1, 0, and 1, resp. a negative, neutral, and positive opinion about each of the 6 traits/aspects, e.g. the use of recreational drugs). There are 5 subcultures that both influence (through the aforementioned genetic operations of mutation and recombination of chromosomes simulating exchange of opinions) and are influenced by its members (since a group is a weighted average of the opinions and actions of its constituents). The objective of this feedback loop is to investigate under which conditions certain subculture sizes emerge, but the model is open to many other kinds of explorations as well.

An agent model is presented that aims to capture the impact of cheap talk on collective action in a commons dilemma. The commons dilemma is represented as a spatially explicit renewable resource. Agent’s trust in others impacts the speed and harvesting rate, and trust is impacted by observed harvesting behavior and cheap talk. We calibrated the model using experimental data (DeCaro et al. 2021). The best fit to the data consists of a population with a small frequency of altruistic and selfish agents, and mostly conditional cooperative agents sensitive to inequality and cheap talk. This calibrated model provides an empirical test of the behavioral theory of collective action of Elinor Ostrom and Humanistic Rational Choice Theory.

Using data from the British Social Attitude Survey, we develop an agent-based model to study the effect of social influence on the spread of meat-eating behaviour in the British population.