ABM for the Social Scientist: A Practical Guide to Model Building and NetLogo - CECAN Ltd CPD Course

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United Kingdom of Great Britain and Northern Ireland

Computational methods have revolutionised the sciences, including the social sciences. Researchers are able to experiment with different hypotheses in silico, investigating the dynamics of complex, interdependent systems. Agent-based models simulate people (or firms or other entities) taking actions influenced by their own characteristics and their social and physical environment. These models are particularly good at modelling the heterogeneity of a population and exploring the implications of the interactions between people and their actions.

This course will guide you through the research process of agent-based modelling in the social sciences: formulating a research question, specifying a model, creating a simulation and interpreting the output. During the course you will build a model that includes personal, social and environmental factors using NetLogo, acquiring basic and intermediate programming skills.

The syllabus includes:

  • Conceptualising agent-based models
  • Operationalising and calibrating from data
  • Experimenting and analysing
  • Interpreting models
  • Verifying and validating

Each step of the research process will be complemented by:

Hands-on sessions of model building in NetLogo, a widely used and powerful language for social science modelling. The sessions are designed in such a way that you will understand the structure of a model and learn to write the program code yourself.

Model development sessions. These sessions will facilitate the development of a model relevant to your research, from conception through specification to first steps of implementation.

At the end of this course, you will be able to see the world through modeller's eyes and start programming your own agent-based models.

Intended Audience

Policy analysts, commissioners of evaluation, professional evaluators, social science postgraduate students and researchers.

Tutor Biographies

Dr Jennifer Badham is Assistant Professor in Social Data Science in the Department of Sociology at Durham University. She originally trained as a mathematician and developed an interest in applying mathematical modelling methods to social policy while working for government and nongovernment health organisations in Australia. Her main research interest concerns the way that social structures affect transmission – of disease, information, beliefs and behaviour.

Dr Corinna Elsenbroich is a Reader in Computational Modelling at the MRC/CSO Social and Public Health Sciences Unit at the University of Glasgow. She is also a member of the Centre for the Evaluation of Complexity Across the Nexus (CECAN) and a Non-executive Director of CECAN Ltd. Corinna is a complexity social scientist interested in developing methods to understand the social world better. She is in particular interested in complex causality, epistemological questions of simulation modelling and developing complexity methods in co-production with stakeholders.

Course Fees (not including VAT)

  • Government / commercial sector: £1,000
  • Staff from educational or charitable institutions: £600
  • Students (including postgraduate researchers): £300

Delegates are required to attend all three days of the course. The above prices are for one three-day ticket. Ticket prices do not include accommodation.

How to Book

Reserve your place by registering and paying via our Eventbrite page:

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