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IMPORTANT NOTICE: This is the website for an earlier offering of NETS 112 that is no longer active. For the excellent current version of the course please visit here.

Networked and Social Systems Engineering (NETS) 112
Fall 2019
Tuesdays and Thursdays 10:30-12, Berger Auditorium, Skirkanich Hall
Prof. Michael Kearns

Jump to the course schedule.


  • What science underlies companies like Facebook, Twitter, Google and Uber?
  • What are the economics of email spam?
  • How much is revealed by who you call, text, or friend?
  • Why do some social networking services take off, and others die?
  • What does game theory have to do with Internet routing?
  • How does Google find what you're looking for... and exactly how do they make money doing so?
  • How might a social network influence election outcomes?
  • How does your position in a social network (dis)advantage you?
  • What might we mean by "algorithmic fairness" or even "algorithmic morality"?

    Networked Life looks at how our world is connected -- socially, strategically and technologically -- and why it matters.

    The answers to the questions above are related. They have been the subject of a fascinating intersection of disciplines, including computer science, physics, psychology, sociology, mathematics, economics. law and finance. Researchers from these areas all strive to quantify and explain the growing complexity and connectivity of the world around us, and they have begun to develop a rich new science along the way.

    Networked Life will explore recent scientific efforts to explain social, economic and technological structures -- and the way these structures interact -- on many different scales, from the behavior of individuals or small groups to that of complex networks such as the Internet and the global economy.

    This course covers computer science topics and other material that is mathematical, but all material will be presented in a way that is accessible to an educated audience with or without a strong technical background. The course is open to all majors and all levels, and is taught accordingly. There will be ample opportunities for those of a quantitative bent to dig deeper into the topics we examine. The majority of the course is grounded in scientific and mathematical findings of the past two decades or less (often much less).

    Fall 2019 is the sixteenth offering of Networked Life. You can get a detailed sense for the course by visiting the extensive course web pages from past years:
    [Fall 2018]   [Fall 2017]   [Fall 2016]   [Fall 2015]   [Fall 2014]   [Fall 2013]   [Fall 2012]   [Spring 2010]   [Spring 2009]   [Spring 2008]   [Spring 2007]   [Spring 2006]   [Spring 2005]   [Spring 2004]

    There was also a greatly condensed version of this class offered to the general public as part of the online education platform Coursera. While the Coursera version is not being offered online this semester, we will make the corresponding videos available throughout the Penn offering, and they are all gathered here.

    Networked Life is the flagship course for Penn Engineering's Networked and Social Systems Engineering (NETS) program. Throughout the course we will foreshadow material that is covered in greater depth in later NETS program courses, but NETS 112 is entirely self-contained.


    At least portions of the following four books will be required reading:

  • Six Degrees: The Science of a Connected Age, by Duncan J. Watts. W.W. Norton, 2003.
  • Micromotives and Macrobehavior, by Thomas C. Schelling. W.W. Norton, 1978.
  • Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, by Cathy O'Neil. Crown, 2016.
  • The Ethical Algorithm, by Michael Kearns and Aaron Roth, Oxford University Press, 2019 (available Oct/Nov).

    The links above are to the Amazon sites for the books, where they are available in inexpensive paperback and e-book formats. The paperback versions will also be available at the Penn bookstore.

    In addition to readings from these texts, there will be frequent articles from the recent scientific and popular literature that will be provided directly on this web page at the appropriate points in the syllabus.


    Prof. Michael Kearns, Course Instructor
    Levine Hall 509
    Office hours: Tuesdays 12-1 PM (right after lecture), or by appointment

    Margaret Ji, Teaching Assistant
    Office hours: Friday 3-4 PM, New College House lobby

    Luke Yeagley, Teaching Assistant
    Office hours: Thursday 8-9 PM, Harrison mezzanine

    Karthik Tadepalli, Teaching Assistant
    Office hours: Monday 3:30-4:30 PM, Levine mezzanine


    Attendance at the main lectures is considered mandatory for all enrolled students. They are held Tuesdays and Thursdays 10:30-12 in Berger Auditorium of Skirkanich Hall. There are no recitations for the course.


    Networked Life has no formal prerequisites, and is meant to be accessible to a broad range of students across SEAS, the College, and Wharton. No computer programming background is required, but students should be comfortable using computers and the Web, and accessing resources on the Internet.

    The course is open to all majors and all levels.


  • Networked Life is one of the courses satisfying the College of Arts and Sciences' Quantitative Data Analysis Requirement.
  • Networked Life can be counted as an official Engineering Elective course in CIS and SEAS.
  • Networked Life can be counted for credit in the Philosophy, Politics and Economics (PPE) and Science, Technology and Society (STSC) programs.

    Please check with your academic advisor in these programs to confirm exactly how you can count the course.


    The main lectures for Networked Life will be in fairly traditional format, including class participation, discussion, and communal in-class experiments. PDF slides for all lectures will be provided, usually at least slightly in advance of the lecture itself.

    There will be two or three homework assignments. These will include simple quantitative exercises, as well as essay questions, computer and web exercises. Collaboration on the homeworks is not permitted.

    There will be a midterm, and a final exam. We may have a quiz or two as well.

    It is anticipated that the homeworks/quizzes, midterm and final will each count for approximately a third of the overall grade.

    Students are encouraged to bring articles, demos, web pages, news events, etc. that are relevant to course topics to the attention of Prof. Kearns. Extra credit will be given if the suggested material is used in the course (see the "Fourth Column" below).


    Except for occasional hard-copy handouts distributed in lectures, all of the material for the course will be posted in the table below. Lecture slides, reading and homework assignments, in-class and out-of-class experiments, due dates, exam information, etc. will all be provided below. The materials posted are initially those from the last offering of the class, and will be gradually updated and possibly altered as we progress through the course. New materials and topics may be added as well. Reading and working ahead are encouraged, just be aware that things may change a bit as we proceed. It is every student's responsibility to monitor this schedule closely and regularly.

    In the assigned readings below, "Watts", "Schelling", "O'Neil" and "Kearns/Roth" refer to the four required texts cited above. Other readings will be directly provided as links to PDF documents. Unless specified otherwise, you should generally try to complete the assigned reading during roughly the period spanned by the dates given in the same row of the table.

    The lecture slides are all in PDF format, but they may often contain links to documents in other formats, including Postscript, JPEG, video, etc. In order to view all of the linked content you may need to be using a computer with viewers installed for these formats. Note that since slides are revised shortly in advance of each lecture date, links to future decks may not yet be active.

    In the "DATES" column of the table below, our current place in the schedule will be highlighted in red.

    "THE FOURTH COLUMN" will be used to put links to class-related materials from the popular media, the web, etc. Extra credit will be provided to those who send me such material if it is used.

    The date for the final exam is Thursday, December 12 at 9AM.

    Tue Aug 27
    Thu Aug 29
    Course Introduction and Overview
    [PDF] [PPT]
    (Rev. 8/26)

    Here is the Coursera course overview video.

    Here is a document containing a brief background survey and our second communal social experiment. Please print them out, complete them (which should only take a few minutes), and return them at the start of the second lecture (Thu Aug 30), as we will analyze the results of the social experiment on the fly in class.

    As sample Fourth Column material, an updated Stanley Kubrik classic.

    Thu Aug 29
    Tue Sep 3
    Thu Sep 5
    Structural Properties of Networks: Introduction
    [PDF] [PPT]
    (Rev. 9/4)

    Please read this lightweight introduction to some course concepts via a network analysis of squash matches.

    Link to the Erdos Number Project website.

    Here are two Coursera videos that are related to this set of lectures:

    What is a Network?

    The Erdos Number Project

    First-to-Field-Agent honors go to Palmer Paul, who found these two papers on Facebook graph structure.

    Tu Sep 10
    Th Sep 12
    Tu Sep 17
    Contagion in Networks
    [PDF] [PPT]
    (Rev. 9/10)
    The following three assigned papers will be discussed in lecture. At a minimum you should know what the main results are, but try to understand as much as you can.

    The Structural Virality of Online Diffusion. Goel, Anderson, Hofman, Watts.

    Structural Diversity in Social Contagion. Ugander, Backstrom, Marlow, Kleinberg.

    Here is a link where you can download NetLogo, a very nice app with many scientific simulations and models. Throughout the term we'll be examining several of the simulations under the Networks section, including this one, which we'll play around in class with.

    Here is a Coursera video related to this topic:

    Contagion in Networks

    Thu Sep 19
    Tue Sep 24
    Machine Learning and Social Networks
    (no slides)

    Can Cascades be Predicted? Cheng, Adamic, Dow, Kleinberg, Leskovec.

    Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook. Backstrom and Kleinberg.

    Private Traits and Attributes are Predictable from Digital Records of Human Behavior. Kosinski, Stillwell, Graepel.

    Thu Sep 26
    Tue Oct 1
    Thu Oct 3
    Navigation in Networks
    [PDF] [PPT]
    (Rev. 9/29)

    During this set of lectures, we will discuss the following five articles.

    An Experimental Study of the Small World Problem, by J. Travers and S. Milgram.

    An Experimental Study of Search in Global Social Networks, by P. Dodds, R. Muhamad, and D. Watts.

    Navigation in a Small World, Kleinberg.

    Identity and Search in Social Networks, Watts, Dodds, Newman.

    The Scaling Laws of Human Travel, Brockmann, Hufnagel, Geisel. (We'll discuss this one only briefly.)

    There are two Coursera videos associated with this lecture:

    Navigation in (Social) Networks

    Navigation in Networks, Revisited

    Here is Homework 1 ( Word format ) (note: updated with two new problems 10/2). It is due in hard-copy format at the start of lecture on Tuesday October 15. Also, reminder: no collaboration of any kind on homeworks.

    Tue Oct 8
    Tue Oct 15
    Thu Oct 17
    How Do Real Networks Look?
    (Rev. 10/7)

    (Reminder: No lecture Thu Oct 10, Fall Break)

    For these lectures, you should read Chapters 2, 3 and 4 in "Six Degrees". (I recommend simply reading the book in its entirety, but will not require it.)

    We will also be discussing the following paper:

    Four Degrees of Separation. Backstrom et al, 2012.

    Here are Coursera videos associated with this set of lectures:

    How Do Real Networks Look? I. Heavy Tails

    How Do Real Networks Look? II. Small Diameter

    How Do Real Networks Look? III. Clustering of Connectivity

    From Repeat Offender Palmer Paul, network science and FC Barcelona. From Field Agent Andy Nguyen, information gerrymandering in social networks.

    Tue Oct 22

    Q&A session with TAs

    To help you prepare for Thursday's midterm, in this lecture the TAs will field questions regarding course material. .
    Thu Oct 24


    The midterm exam will be held during class, and will be closed book and closed note. It will cover all material to date.

    To help you prepare for the midterm, here are past midterm examinations (some but not all with solutions) from 2018   (solutions here) , 2017   (solutions here) ,   2016,   2015,   2014,   2013,   2012,   2011,   2010,   2009,   2008,   2007, and 2006. Please remember that course content and schedule changes from year to year, so these midterms definitely cover material we have not yet, or will not, discuss this term; and conversely, there are new topics we've introduced this term that are not represented on these past midterms.

    Tue Oct 29
    Thu Oct 31
    Models of Network Formation
    [PDF]   [PPT]
    (Rev. 10/28)

    Coursera videos associated with these lectures; we will only discuss Erdos-Renyi and Preferential Attachment in class, but you are also responsible for the clustering models video:

    Models of Network Formation I. The Erdos-Renyi Model

    Models of Network Formation II. Clustering Models

    Models of Network Formation III. Preferential Attachment

    For those of you that would like to experiment with the NetLogo package used for some course demos, you can download it here.

    Tu Nov 5
    Incentives and Collective Behavior
    [PDF]   [PPT]
    (Rev. 11/4)

    Read Schelling, "Micromotives and Macrobehavior", Chapters 1, 3 and 4.

    Coursera video associated with this lecture:

    Towards Rational Dynamics in Networks

    Th Nov 7

    Introduction to (Networked) Game Theory
    [PDF]   [PPT]
    (Rev. 11/7)

    Coursera videos associated with this lecture:

    Basics of Game Theory

    Games on Networks: Preview

    Tu Nov 12
    Th Nov 14

    On Tuesday, November 12 we will have a special guest lecture by Prof Duncan Watts, whose work we have read about several times and who has recently joined the Penn faculty. Attendance is mandatory.

    Here are slides and the paper from Watts' talk.

    There will be no lecture on Thursday, November 14.

    Tu Nov 19
    Th Nov 21
    Networked Games: Coloring, Consensus and Voting; Network Formation Games
    [PDF]   [PPT]
    (Rev. 11/19)

    Here are Homework 1 solutions and grading guidelines.

    Read the following article associated with these lectures:

    Experiments in Social Computation, MK.

    Coursera videos associated with these lectures:

    Games on Networks: Coloring and Consensus

    Games on Networks: Biased Voting

    Network Formation Games

    Tu Nov 26
    Algorithmic Privacy
    [PDF]   [PPT]

    NOTE: due to the short time remaining in the semester, we will not be covering the book "Weapons of Math Destruction", but we will be reading "The Ethical Algorithm" as per the schedule below.

    Reading: "The Ethical Algorithm", Introduction and Chapter 1.


    Tu Dec 3
    Algorithmic Privacy and Fairness

    Reading: "The Ethical Algorithm", Chapter 2.

    Here is Homework 2 ( Word format ) It may be updated with one or two additional problems, so please be sure you complete the latest version. It is due in hard-copy format any time up to Thursday, December 19, details TBD.

    Also, reminder: no collaboration of any kind on homeworks.


    Th Dec 5
    Algorithms, People and Game Theory

    Reading: "The Ethical Algorithm", Chapters 3 and 4.


    Th Dec 12


    Here are solutions and grading guidelines for the midterm. The average was 83.6 and the standard deviation was 11.

    Here are some past final exams, some with solutions, to help you study. Please note that some of the questions are on topics we did not cover this year, and that we covered topics this year that are not represented on the exams.

    [2004]   [2005]   [2006]   [2007]   [2008]   [2009]   [2011]   [2012]   [2013]   [2014]   [2015]   [2016]   [2017]   [2018]