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2015-09-21
ETH Zürich
Modeling and Simulating Social Systems with MATLAB
Lecture 1 – Course Introduction
Computational Social Science
Olivia Woolley, Stefano Balietti, Dirk Helbing
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Lecture 1 – Contents § Content, rules, and goals of the course
§ Short motivation on Modeling and Simulation § What is MATLAB? § MATLAB basics
§ Next week: § Plotting/Statistics in MATLAB § Introduction to Git
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Modelling and Simulating Social Systems with MATLAB
Weekly lecture with exercises, each session will be split into about 40 minutes lecture and 60 minutes exercises / project work. We will put the lecture slides and other material on http://www.coss.ethz.ch/education/matlab.html and we will use GitHub (more on that later): github.com/msssm
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How to contact us
§ in the lecture; please do not hesitate to approach us with any questions you might have
§ via email to
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Mailing List § Send an email to:
[email protected] § with text:
SUBSCRIBE msssm Your Name § E.g.
SUBSCRIBE msssm Karsten Donnay
§ Text to unsubscribe:
SIGNOFF msssm
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Purpose of the Mailing List § Foster cooperation among students
1. Discuss technical issues
2. Discuss organizational issues
3. Share code
4. Share references to literature
5. Share references to datasets
6. Form and communicate groups
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Rules of the Mailing List 1. Be nice.
2. Be collaborative.
3. Only small attachments. Add links to external resources.
4. Do not spam.
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Examination Format
Students earn their credit points by:
1. Implementing a model / running simulations / analyzing data from the social science literature in MATLAB
2. Submitting a short proposal specifying their project
3. Producing a seminar thesis (up to 15 pages)
4. Presenting the results it in a 15 minute seminar talk (The thesis should include a discussion of the model, its theory and properties, details of the simulation, parameter dependencies, results from data analyses, but also possible practical implications.)
§ Submission of the work through GitHub: github.com/msssm (more on that later on)
(also see the course description)
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Seminar thesis
Studying a scientific paper and/or a data set
Reproducing and extending results / running a simulation in MATLAB
Writing a report and giving a talk
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Project § Implementation of a model from the social science
literature in MATLAB § During the next 2-3 weeks:
§ Form a group of 2-4 students
§ Decide together on a topic and research question
There are a lot of different project topics available on the Project section of the course website but we encourage you to realize your own ideas for example with one of the datasets listed.
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Project § If you are looking for inspiration:
§ A number of reports from the previous course are linked on the Project section of the website
§ Take a look what they did, maybe you would like to build up on their work…
§ If you are a Master/PhD student: § Your project can, of course, be related to your research
topic
Please approach us in class or write us an email if you have any questions.
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Project § Procedure:
§ Organize yourself into groups (use the mailing list!)
§ Carefully select a topic (and corresponding papers)
§ Think about which particular question you want to study
§ Each group has to submit a short 1-2 page proposal that very briefly describes what they are planning to do
§ More information will follow in the next lectures
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Flash Talks Each group will have to present their proposal in the
form of a flash talk:
§ Only 1 slide!
§ Only 3 minutes! (plus 2 minutes questions/feedback)
§ The entire 5th lecture (19 October) is reserved for these flash talks
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Projects from previous semesters
Sugarscape Civil violence Group dynamics
Trust Facebook social networks
Space syntax
Pedestrian dynamics Cycling strategies Tumour growth
Segregation Cancer Traffic dynamics
Swarms Sailing strategies Migration
Flocks Cockroaches Arab Revolutions
Civil war Queuing models Synchronized clapping
Game theory tournament
Game theory Language formation
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Schedule of the course § The first and second lectures will be on the basic
functionality of MATLAB: matrix operations, data structures, conditional statements, statistics, plotting, etc.
§ In later lectures, we will introduce various modeling approaches from the social sciences: dynamical systems, cellular automata, game theory, networks, multi-agent systems, …
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Schedule of the course 21.09. 28.09. 05.10. 12.10. 19.10. 26.10. 02.11. 09.11. 16.11. 23.11. 30.12. 07.12. 14.12.
Introduction to MATLAB
Introduction to social-science modeling and simulations
Working on projects (seminar thesis)
Handing in seminar thesis and giving a presentation
Flash Talks
Modeling overview
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Schedule of the course § Please take note of the dates for the hand-in and
the oral presentation of your projects:
§ Deadline for project proposals: Sunday 18 October 2014 at midnight
§ Flash talks: Monday 19 October 2014
§ Deadline for project reports: Friday 11 December 2014 at midnight
§ Oral project presentations: 14 December to 16 December 2014
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Goals of the course: 1. Acquiring understanding of the basics of MATLAB.
2. Attaining practical knowledge of MATLAB necessary to run computer simulations.
3. Understanding basic properties of social systems.
4. Acquaintance with main quantitative modeling approaches for social systems.
5. Implementing (simple) models of social systems, replicating and extending established models.
6. Learning to pose a scientific research question
7. Becoming confident in communicating scientific results in an academic context.
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Requisites of the Course § Highly interdisciplinary course: Physics, Sociology, Game
Theory, Biology, Computer Science, Software Engineering…
This course requires:
1. Hard work
2. Curiosity and creativity
3. Interest in scientific methods
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MATLAB § Why MATLAB?
Language is quick to learn, easy to use, rich in functionality, good plotting abilities.
§ MATLAB is commercial software from MathWorks, but there are free MATLAB clones with limited functionality (Octave and Scilab).
§ Python SciPy packages similar to MATLAB
§ MATLAB can be downloaded from ides.ethz.ch
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What is a Social System?
§ A set of interdependent relationships, customs, and institutions that constitute a society. (Oxford English dictionary)
§ A social system is the patterned series of interrelationships existing between individuals, groups, and institutions and
forming a whole. (Merriam-Webster dictionary)
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What is a model?
§ A reduced abstraction of reality aimed at understanding certain components of a more complicated/complex whole.
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On Exactitude in Science . . . In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province. In time, those Unconscionable Maps no longer satisfied, and the Cartographers Guilds struck a Map of the Empire whose size was that of the Empire, and which coincided point for point with it. The following Generations, who were not so fond of the Study of Cartography as their Forebears had been, saw that that vast Map was Useless… Source: Jorge Luis Borges, Collected Fictions, Translated by Andrew Hurley Copyright Penguin 1999
What is a model?
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Introduction to Modeling and Simulations § Modeling and simulations allow us to formalize,
discover and even predict real-world phenomena.
§ Simulations are the instantiation of a process specified by a formal model.
§ Simulations allow us to study models that are not analytically tractable.
§ Simulations can also be very entertaining (a nice byproduct but not the main purpose of the course).
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Emergence and Simulations § Explaining macro-phenomena based on micro-
mechanisms
§ Especially relevant in a complex system.
§ Simulations can capture “Emergence”:
“Interactions among objects at one level give rise to different types of objects at another level.”
“The whole is more than the sum of its parts.”
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Emergence and Simulations
Courtesy of Iain Couzin
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Modeling and Simulation
Model
Social processes
Simulated data
Collected Data
Source: Gilbert and Troitzsch (2005)
Abstraction
Simulation
Data gathering
Similarity
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Emergence of Tokyo transportation network
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Fig. 1 Network formation in Physarum polycephalum.
Atsushi Tero et al. Science 2010;327:439-442 Published by AAAS
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Fig. 2 Comparison of the Physarum networks with the Tokyo rail network.
Atsushi Tero et al. Science 2010;327:439-442 Published by AAAS
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Fig. 4 Network dynamics for the simulation model.
Atsushi Tero et al. Science 2010;327:439-442 Published by AAAS
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References § Gilbert, N. and Troitzsch K.G. “Simulation for the Social Scientist” 2nd
Ed. Open Uni. Press (2005)
§ Epstein J.M. and Axtell R. “Growing Artificial Societies. Social science
from the bottom up” MIT Press (1996)
§ Epstein J.M. “Generative Social Science” Princeton Uni. Press (2006)
§ Tero, Atsushi, et al. "Rules for biologically inspired adaptive network
design." Science (2010).
§ Emergence: https://www.youtube.com/watch?v=aEaZHWXmbRw