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ECPR Joint Sessions 2020 Sciences Po Toulouse

WB108 - Tools for the Analysis of Complex Social Systems: An Introduction

Instructor Details

Instructor Bio

Lasse Gerrits is professor in political science at the University of Bamberg. His research focuses on the nexus of technology, policy and politics.

He is interested in methodological issues with regard to social complexity and the ways in which this complexity can be unboxed.

Lasse has published extensively on this topic in relationship to qualitative comparative analysis, critical realism, social complexity and qualitative methods.

He also has ample experience in applied research with, among others, railway companies all over Europe, and with many local and regional planning authorities.

Twitter  @ComplexGov


Course Dates and Times
Monday 17 –  Friday 21 February, 14:00 –17:30 (finishing slightly earlier on Friday)
15 hours over 5 days
Prerequisite Knowledge

You don’t need to have followed any particular course prior to this one. However, we expect you to be familiar with the basic operations of qualitative and quantitative data collection and processing, and to have a basic understanding of case-based research approaches. 

Short Outline

Many researchers will agree that the world is a complex one that is hard to grasp – and even harder to map and analyse in social science research

How that complexity can be unboxed is something we will address in this course.

The course will introduce academic researchers and professionals in the realm of (policy) evaluation to the main tools for the analysis of complex social systems. We will cover various aspects of social complexity, including structural features, individual behavior and the role of relationships.

The course favours a multi-method approach and welcomes people from qualitative and quantitative research traditions.

You will learn:

  • system dynamics modelling
  • agent-based modeling
  • dynamic network analysis
  • case-based modelling
Long Course Outline

Why do certain political and policy processes stall while others that look similar move ahead without trouble?

Why is it that certain political systems survive but others don’t?

Why is it still so hard to predict how policy measures will pan out in the real world?

The keyphrase is causal complexity. Causal complexity means that chance and randomness plays an important role in what we observe, that similar cases may follow dissimilar routes – and the other way around, of course – that the whole is more than the sum of the parts, and that social processes develop in a non-linear fashion.

Mapping and analysing social complexity is hard. This doesn’t mean that we should give up and go home. On the contrary, there is a whole range of tools and approaches that can be used to unbox this causal complexity.

This course focuses on those tools. We will discuss the nature of causal complexity and will work with various powerful instruments to map, analyse and interpret causal complexity.

The course is open to academic researchers and professionals in the realm of (policy) evaluation and research.


Day 1

We focus on the nature of complex causality. We discuss where that complexity can be found and how it should be understood. To this end, we will look into issues of epistemology and ontology. We will also discuss what it means to do case-based research. While this is not a theoretical course, it is still important to get on the same page when doing actual research. 

Day 2

We focus on macro structures of social systems. We will learn to trace and map such structures with a technique called systems dynamics modelling. This approach will teach you how to draw causal loop diagrams and, if necessary, to explore and simulate various possible outcomes of the political and policy processes you are studying. System dynamics modelling shows how causes can turn into consequences, or the other way around, and how certain processes can be self-defeating or surprisingly effective. 

Day 3

We change focus from the macro- to the micro-level. We look into human behaviour, and how it can be analysed and understood as a matter of interactions between humans, using a tool called agent-based modeling. This offers a convenient way of exploring interactions and their (emergent) outcomes. It is also helpful in understanding the unpredictability of social complexity. 

Day 4

We focus on social networks. As we are increasingly aware of the many connections between people, we need to get acquainted with the tools of network analysis, in particular dynamic network analysis. We learn how to structure, differentiate and map relationships, and how to interpret the evolution of networks over time. 

Day 5

We connect all the dots from the previous parts, combining the insights gained to build a case-based understanding of social complexity. With the aid of two tools, Complex-it and un-code, we will explore the ways in which we can arrive at research that does justice to social complexity.


As you may gather from the description, the course takes a mixed-methods approach. As such, it we welcome researchers and evaluators from different strands, qualitative and quantitative. The only thing we ask from you is that you think about your research as being contextual, i.e. case-based.

Please note You are kindly requested to bring in examples, data and questions from your own research to make this course work for you. While we will occasionally use pre-prepared datasets for certain exercises, the course and most exercises will focus on your research. If you don’t have any data yet, you can still participate as long as you have a conceptual model and / or theoretical framework to work with. In the end, the course can only be useful for you if you want to get something out of it. The Instructor and TA will be available to answer your questions and to deal with any issue you may have with your own research. 

Day-to-Day Schedule

Day-to-Day Reading List

Software Requirements

All listed software is freeware and / or open source so you don’t need to buy licenses.

Download Venism & NetLogo, and use the online versions of Complex-It and Un-code.

Please note The software will be used to support your research but this is not an in-depth course on how to use it. We will discuss the basics so that you can take it from there. 

Hardware Requirements

Please bring your own laptop.

The required software runs on all contemporary hardware, though we have had a couple of problems with Vensim and Netlogo on Macs. If you're a Mac user, please check these work without problems and contact the Instructor if you have any questions. 

The following other ECPR Methods School courses could be useful in combination with this one in a ‘training track .
Recommended Courses Before

Summer School

  • Introduction to Case-Based Research and Set-Theoretic Thinking
  • Case Study Research: Method and Practice
  • Multi-Method Research: Techniques and Applications

Winter School

  • Advanced Qualitative Data Analysis
  • Philosophy and Methodology of the Social Sciences
Recommended Courses After

Summer School

  • Longitudinal Research Designs Qualitative Approaches
  • Qualitative Comparative Analysis

Winter School

  • Qualitative Comparative Analysis
  • Introduction to Applied Social Network Analysis
  • Advanced Sequence Analysis
  • Event History and Survival Analysis

Additional Information

Disclaimer

This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc). Registered participants will be informed in due time.

Note from the Academic Convenors

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, contact the instructor before registering.


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