A Primer on Complexity: an Introduction to Computational Social Science

A Primer on Complexity: An Introduction to Computational Social Science

Shu-Heng Chen Department of Economics National Chengchi University Taipei, Taiwan 116 [email protected]

1 Course Objectives

This course is to enable the students of social sciences to have some initial experiences of computational modeling of social phenomena or social processes.In this regard, it severs as the beginning course for preparing students of social sciences to have computational thinkingof social phenomena.On the other hand, the course is also to serve as a beginning course for the students of computer science or students with a strong taste for programming andmodeling who are, however, very curious of social phenomena, and want to see whether they can develop their talents in the axis of social sciences.

2 Course Description

National Chengchi University is internationally well-known for its social sciences, but what are the natures of social sciences, and, to what extent, do they differ from sciences? Are these differences fundamentally or just superficially? The current social sciences are divided into economics, business, management, political sciences, sociology, psychology, public administration, anthropology, ethnology, religion, geography, law, international relations, etc. Is this division necessary, logical? When a social phenomenon is presenting itself to us, such as populism, polarization, segregation, racism, exploitation, injustice, global warming, income inequality, social exclusiveness or inclusiveness, green energy promotion, anti-gouging legislation, riots, tuition freeze, mass media regulation, financial crisis, nationalism, globalization, will it identify itself: to which sister discipline it belongs? Economics? Psychology? Ethnology? If the purpose of social sciences is to enhance our understanding (harness) of social phenomena, and hence to enable us to develop a good conversation quality among cit- izens of the society from which the social phenomena emerge, then we probably need to promote good conversations among social scientists first. This is the so-called social science in an interdisciplinary context. Without sufficient conversations among social scientists first, we are afraid that the students of the current social sciences with so many disciplines may learn a lot, but in a rather fragmental way.

1 Therefore, while entering into different gates of the social science castle, maybe it is useful to have a more generic, comprehensive, jargon-free pursuit of what social science exactly is. What are the rudimentary elements? What are their generic properties? This fundamental pursuit is the focusing subject of this course, which actually makes social science a coherent family. The course provides two answers to this fundamental pursuit.First, as the title of the course suggests, social sciences deal with social phenomena with different degrees of complexity. Some examples from the magnum opus of Thomas Schelling (1921-2016) “Micro Motives and Macro Behavior” (Schelling, 1978) are sufﬁcient enough to illustrate whatwe mean by complexity in social phenomena. In Week 5, we will review his fa- mous work on the segregation phenomenon observed in many metropolitan areas, such as New York, Chicago, and Los Angeles. Why do people of different races tend to be lumped together in residence? Is it because they are not tolerant enough for different ethnic groups? If individually they each are quite tolerant of the unlike people, would that be surprising if collectively they don’t seem so? This segregation example shows us one lesson: knowledge of individuals may help us little in predicting what would happen ’as a whole’, and this is what makes social science intriguing, fascinating, and complex. However, just in a verbal way, the word complexity does not automatically unveil all deep functioning mechanisms underlying complex social phenomena.To know the “chemistry” which can add up all simple things in a complex form, we need to simulate these social phenomena. Without going deep into the social process and successfully simulating the observed phenomena, our eyes and minds are frequently under great expo- sure to being deceived by what may seem obvious. Nevertheless, as we shall experience in this class (say the Game of Life, Week 2), paper and pencils are far less than enough for simulating social phenomena, even though what we need to consider is just a small-scale primitive society. Hence, here comes our second response (answer) to the fundamental pursuit, i.e., computational social science, the subtitle of the class. The idea is to take full advantage of the great advancement in high-performance computing to tackle complex social phenomena. Having said that, this class does not intend to challenge or scare away those students with programming phobia, most likely, students from social science departments. By no means we will teach anything in programming seriously. In fact, the current development of computational social science already makes it much more approachable with so many easy-to-use software (languages), and NetLogo is one of them (Railsback and Grimm, 2011; Hamill and Gilbert, 2015; Wilensky and Rand, 2015). In this class, we shall use NetLogo to make students have a quick grasp of the three rudimental elements of all social phenomena, namely, agents, also called actors, decision- makers (their personal traits and behavioral rules), social embeddedness (institutions, cultures, laws, history, spatial surroundings), and social interactions. As we shall see in many examples, aided by NetLogo, these three rudimental elements not only are able to simulate many interesting social phenomena but can also overarch various sister disciplines of the social science family. At the end of the class, we shall leave all students a chance to answer the questions which we begin with. First, is it really a fundamental difference between science and social science? Second, is it really necessary to have so many different treatments for the same social phenomena with so many different disciplines, from A to Z; would it be better if we can have a coher-

2 ent or united framework so that we would be only interestedin things by its relevancy not by its disciplines. Third, can we say something about the future of social science, in particular, in light of shaping a good society?

3 Class Schedule

General Speciﬁcation:

1. The student is expected to spend 9 hours per week on this course, which means a 6-hour preparation and review work plus 3-hour class attendance.

2. The assignment (the reading and the computer simulation exercises) will be given at the end of each ppt of the lecture.

3. The student is required to reﬂect upon the lecture received the week and propose questions, comments, or observations before the lecture of the next week. This “weekly report” needs to be submitted to the web as indicated in the class. The late submission will not be accepted.

Weekly Progress:

1. Week One (Lectured on Feb 24, 2021): Background, History, and All Warm-Ups:

(a) Let us begin the story with a genius, John von Neumann (1903-1957) (b) When Social Science become computational and Computer Science become biological? (c) A fascinating history of computational social science

2. Week Two (Lectured on March 3, 2021): John Conway and His Game of Life: CSS coming to the 1970s

(a) How simple things get so complex and hard to predict? (b) Can Life extend without limit? Can you win the award? (c) It is all in NetLogo

3. Week Three (Lectured on March 10, 2021): Stephen Wolfram and New Kind of Science: CSS coming to the 1980s

(a) Butterﬂy Effect: Sensitivity to small changes (b) Small is Big: There is nothing unimportant. (c) Identify new types of social phenomena: Systematic way doing social science (d) A ﬁrst simulation for interesting social dynamics: On the edge of chaos (e) NetLogo, Computer Science, Cellular Automata

4. Week Four (Lectured on March 17, 2021): Sustainable Development and Ecological Balance

3 (a) Uri Wilensky and his perception of science education: Low threshold and high ceiling (b) Wolves and sheep in meadows (c) Alfred Lotka (1880-1949) and Vito Volterra (1860-1940) (d) Predatory-and-Prey Dynamics: Lotka-Volterra Equation (e) NetLogo Models Library: Sample Models/Biology, Wolf Sheep Predation (Wilen- sky and Rand, 2015, Chapter 4)

5. Week Five (Lectured on March 24, 2021): Segregation in Metropolitan Areas

(a) Thomas Schelling: The 2005 Nobel Laureate in Economics (b) Why people with different ethnic groups choose different residential concen- tration? (c) Thomas Schelling and his Segregation Models (d) NetLogo Models Library: Sample Models/Social Science, Segregation

6. Week Six (Lectured on March 31, 2021): Tutorial on Netlogo Programming (lectured by Dr. Tina Yu). Please bring your own computer.

7. Week Seven (Lectured on April 7, 2021): Public Health and Epidemiology

(a) AIDS, SARS, and Bird Flu (b) NetLogo Models Library: Sample Models/Social Science, AIDS

8. Week Eight (Lectured on April 14, 2021): Efﬁciency and Equity: The El Farol Bar Problem

(a) Brian Arthur and the El Farol Bar (b) Congestion and idle capacity: Too much and too little (c) Social Exclusion (d) NetLogo Models Library: Sample Models/Social Science, El Farol

9. Week Nine(April 21, 2021) Midterm Exam

10. Week Ten (Lectured on April 28, 2021): Trafﬁc in the High Way

(a) Drivers’ behavior and Trafﬁc (b) NetLogo Models Library: Sample Models/Social Science, Trafﬁc Basic, Grid, 2 lines

11. Week Eleven (Lectured on May 5, 2021): Gossip and Social Networks

4 (a) Gossip: Everybody like it so long as it is not about you (b) Social network: Your Facebook, Skype,... (c) How fast gossip can go: Significance of social networks (d) NetLogo Models Library: Sample Models/Social Science, Rumor Mill 12. Week Twelve (Lectured on May 12, 2021): Time and Hero: Who Made Whom? (a) Reynold Boyd and His Flocking Project (b) Swarms and Their Intelligence (c) Who made a hero? Nobody, it is all self-organizing! (d) NetLogo Models Library: Sample Models/Biology, Flocking 13. Week Thirteen (Lectured on May 19, 2021): School’s Anniversary Celebration 14. Week Fourteen (Lectured on May 26, 2021): Great Minds Think Alike (a) It is all done by tacit agreements (b) What we can learn from fireflies? (c) NetLogo Models Library: Sample Models/Biology, Fireflies 15. Week Fifteen (Lectured on June 2, 2021): From Gossip Network to Financial Stability (a) If you don’t do it now, you will regret it. (b) Stock market, foreign exchange market, should government intervene? (c) Natural of intervention (d) NetLogo User Community Models: Artificial Financial Markets 16. Week Sixteen (Lectured on June 9, 2021): From Interpersonal Relation to the Formation of Culture (a) Robert Axtell, one of the BACH group (b) Homophily: Which classmates you are most close to, why? (c) Cultural Formation: Schelling-Axtell Model (d) NetLogo Models Library: Sample Models/Social Science, Party (e) NetLogo User Community Models: Dissemination of Culture 17. Week Seventeen (Lectured on June 16, 2021): Tutorial on Netlogo Programming II (lectured by Dr. Tina Yu). Please bring in your own computer. (a) Sakoda’s Social Interaction Models 18. Week Eighteen (Lectured on June 23, 2021): Final Exam: In-Class Presentation

5 4 Teaching Approach

The course will be taught in English. The course will proceed in lectures. All lectures are prepared in power points, and the students will be able to get these power points before or after the classes. Most lectures will also be accompanied by the computer simulation using the software NetLogo. Students are encouraged to use skype to interact with the instructor between classes.

5 Teaching Assistant Tasks

The teaching assistant shall help the instructor to supervise and assist students’ term project progress. Assistant shall assist the instructor in classroom preparation, such as the projector, internet connection, etc. Assistant shall help instructor to grade the term project and help answer various administration problem associated with the class, such as classroom change (if needed), information announcement, lecture notes upload, etc.

6 Course Requirements and Grading Standards

The evaluation of the student performance will be based on the following three main- stays.

1. In-class participation (30%): The student is expected to submit comments or questions during the lecture online, and their questions and comments will be used to motivate and encourage further in-class discussions.

2. Midterm Exam (30%): The midterm exam will be designed as an explorative take-home exam. The questions will be essay style, and the student is expected to surf over the internet using various google engine to prepare their answers to the questions.

3. In-class presentation of the group projects (40%): The students are expected to form their own group, with no more than 3 team mem- bers, for working on the term project. The term project is characterized by the social simulation demonstrations of the corresponding social phenomena. The students can apply NetLogo or any other social simulation tool to model and simulate any social phenomenon which interests them. In case that students cannot find anything that they are capable of modeling and simulating, the last resort will be a set of defaults with easily-modifiable codes supplied by the instructor. In the lat- ter case, the students can follow either Hamill and Gilbert (2015) or Wilensky and Rand (2015), and pick up a subject from there; the source codes will be provided by the instructors. In the last two weeks, the students are required to give an in-class power-point presentation. To make sure what to be demonstrated are actually pre- sentable, the students are encouraged to discuss their ideas with their instructors in class or in office hours.

6 7 Textbooks and References

There is no formal textbook available for this class. For the term-project purpose, the students are expected to have either Hamill and Gilbert (2015) or Wilensky and Rand (2015), depending on which exercise they would like to take. The instructor will provide students the source codes required to do any project in these two books. In addition, the NetLogo library is the main source of readings. The link is as follows. http://ccl.northwestern.edu/netlogo/ There are also a lot of supplementary materials available for students who like to learn more on their own. Some of these materials can be found in the lecture notes (the power points); some are available upon request.

8 Course Related Links

The most important link to this class, which students are required to visit very often is the ofﬁcial website of NetLogo: http://ccl.northwestern.edu/netlogo/

9 Ofﬁce Hours

The ofﬁce hours are (a) Monday 3:00-5:00 pm (b) Friday 3:00-5:00 pm (c) by appointment. The ofﬁce is #271646, 16F, General Building, South Tower.

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