Modelling Social Interaction in
Information Systems (MSIIS)
10 sessions over one week: Monday 3/7/17 to
Comprising 2hr morning session +
3hr afternoon session every day (timings to be arranged).
Location: University of Szeged, room to be arranged.
Lecturer: Dr David Hales (www.davidhales.com
In human societies individuals, through social interaction, generate
collective properties such as norms, cooperation and exchange. In
animal societies evolved behaviours can solve complex optimisation
problems through individual rule following. Computer systems are
increasingly distributed. Networks link nodes that serve users and
carry out computations. Collectively, system level properties emerge
rather than being centrally controlled. This is similar to how human
and animal societies operate. Recent innovations such as
Bittorrent and Bitcoin employ distributed algorithms that relate to
social, economic and biological models.
In this course we will study both theoretical concepts about social
interaction and models that embody them including:
Ideas will be illustrated by running, and experimenting with,
agent-based models, which students can download and run on their own
- Agent-based models, cellular automata, complex systems
- Artificial life, game theory, evolution and co-evolution
- Cooperation and collective action
Schedule: The course will take an intensive form over one
week (5 days). Most days will comprise a 2hr morning (lecture /
theory) session and a 3hr afternoon (practical / task orientated)
Prerequisites: The course assumes a basic understanding of
computer programming concepts (in any programming language) . It is
also assumed that students will be open to ideas traditionally
outside of computer science such as social science and economics but
no prior knowledge will be assumed of these areas. Students should
have access to a laptop on which NetLogo should be installed (which
they should bring to all sessions). NetLogo can be installed from: https://ccl.northwestern.edu/netlogo/
Assessment: There will be no formal exam. Students will be
assessed based on worksheets completed during the last two days in
the practical sessions.
Aims (the course aims to):
Objectives (by the end of the course students will be able
- Give students an overview of some ways that social interaction
in both social systems and computer systems can be modelled and
- Equip students with the ability to critically assess work
within the area of modelling social interaction.
- Provide students with historical context covering some of the
motivations, intellectual traditions, seminal works and people
associated with modelling social interaction.
- State several significant techniques used to model social
interaction in information systems.
- Understand and describe some seminal Agent-Based Models that
illustrate social interaction theories.
- Critically assess and describe some of the major published
work from the scientific literature in the area.
- Run, experiment with, and modify, models in the NetLogo
Background reading and software:
Software (these should be installed on the student laptop
and brought to all lectures and practical sessions):
Papers (these should be read by students before the course
- NetLogo simulation language (which is bundled with many
example models): https://ccl.northwestern.edu/netlogo/
- Golly cellular automata simulator (includes Conway's game of
life and many others): http://golly.sourceforge.net/
- The R statistical environment (can be used for producing plots
from data): https://www.r-project.org/
Books (these are not required reading but provide wider
background and will be referred to in some of the lectures):
- Gilbert, N., Troitzsch K. G. (2005) Simulation for the social
scientist. Second Edition. Milton Keynes, Open University Press.
[a book about agent-based simulation for social scientists by
leaders in the field who are both sociologists with extensive
- Flake, G. (1998) The Computational Beauty of Nature. MIT
Press. [nice book on self-organisation and other complexity
aspects covered or touched on in some of the lectures]
The course will take an intensive form over one week (5 days).
Most days will comprise a 2hr morning (lecture / theory) session
and a 3hr afternoon (practical / task orientated) session. Slides
and other materials will appear here closer to the course start.
Day 1. Introduction and overview.
Lecture: Some basic concepts. Emergence, self-organisation,
agent-based models, cellular automata, NetLogo.
Practical: Explore discussed models in Netlogo library (guided by
Day 2. Schelling’s segregation model.
Lecture: A detailed look at the segregation model. Exploring the
behaviour of the model systematically.
Practical: Experiment with model in NetLogo and complete worksheet
Day 3. Cooperation and Bittorrent (a double lecture day)
Lecture: The problem of cooperation and how it relates to social /
computer systems. Some concepts from game theory. The
Prisoners’ Dilemma game. Axelrod’s tournaments. Bittorrent and how
it uses incentives.
Lecture: Overview of Bittorrent file-sharing protocol; How the
protocol relates to cooperation theory.
Day 4. Evolution, co-evolution and artificial life.
Lecture: Evolution in general, evolutionary algorithms, genetic
algorithms, co-evolutionary systems, interaction structures other
than mean-field, concept of an ESS, evolving cooperation on a
cellular automata. Nowak lattice model.
Practical: Experiment with lattice model to complete worksheet tasks
Day 5. Riots and Ethnocentrism.
Lecture: Granovetta’s riot model. Axelrod and Hammond’s
Ethnocentrism model. Other recent ethnocentrism models.
Activity: Experiment with models to complete worksheet tasks