CAS CS 591 - Fall 2016 - Networks and Markets: Theory and Applications

Course Overview: Recently, the concept of a network has outgrown the narrower engineering mindset of a collection of interconnected machines to become more broadly relevant in a variety of applied settings which feature connectedness. Biological networks, social networks, online advertising networks, and networks involving hyperlinks, i.e., the WWW, are all examples of domains in which the theory and practice of networking science has now being applied. In parallel with this trend is the rise of online markets as a mediation point for commercial activity. Beginning with the advent of Internet platforms like eBay that employ online auctions, are many fascinating new markets: pay-per-click advertising markets, prediction markets, and two-sided platforms such as Uber and Airbnb. All of these application domains draw deeply on established methodologies that are highly familiar to computer scientists, notably graph theory and algorithms. However, they also build on theoretical foundations that is often unfamiliar territory to computer scientists, such as auction design, mechanism design, and the theory of matching markets. Finally, many important new technologies incorporate a mix of networks and markets, including information networks and recommender systems. In this class, we will build on the highly successful undergraduate text of Easley and Kleinberg to learn about the underlying theory of networks and markets, understand how modern-day digital applications connect to these foundations, and conduct our own independent projects to explore an aspect of a digital market more deeply.

In this class, we will consider networks and markets from a broad and inter-disciplinary perspective, drawing primarily from insights from the Computer Science, Economics, and Marketing communities. This course is designed for students who are potentially interested in either pursuing a career in or conducting research related to online networked platforms. Please note that this course is not about entrepreneurship per se, but will provide useful background for prospective entrepreneurs. The capstone project of the course will be a research effort, conducted by teams of two or three, in which students conduct a quantitative measurement-driven analysis of a computational aspect of an e-commerce firm or of consumer behavior with respect to an e-commerce marketplace.

Prerequisites: This course is designed for declared CS majors who are fulfilling 400-level electives, as well as Masters students and entering Ph.D. students. CS 112, CS 131, and some knowledge of probability and statistics is required. CS 330 is suggested as a co-requisite. While students' backgrounds will vary, it is expected that students are nearing completion of an undergraduate CS major or are beginning their graduate studies. Seniors who are not CS majors should seek the instructor's permission to enroll.

Lectures: Tues/Thurs 12:30-2:00, CAS 237.
I expect students to come to class, to come on time, and to be prepared to actively engage in class discussion.
I will be eliciting responses from all students to hear their opinions.

Instructor:  Prof. John W. Byers
Email: byers @ cs . bu . edu [preferred]
Office Hours (Fall 2016): Open hours: Tues 2-4
By prior appointment only: Wed 10-11.
For technical questions beyond what Piazza can answer (see below), or when you need a consultation.
During office hours, I'll answer my phone at 617-353-8925.
Other times, I generally let phone calls go to voicemail. Please send email instead.

Instructor Bio:

Textbook and Readings

Primary Text: "Networks, Crowds, and Markets: Reasoning About a Highly Connected World", by Easley and Kleinberg. ISBN: 9780521195331

Additional Readings:


We will be using Piazza for all discussions outside of class. Rather than emailing questions about the class to me, I encourage you to post your questions on Piazza, where you are also welcome to answer questions posted by others. Our class page is located at: Please go there to sign up today. We will also use Piazza to post announcements, homework assignments, etc.
Course Requirements and Grading: There will be three components of the grade in the class: For class, we will be drawing primarily from the Easley-Kleinberg textbook, but as this is an introductory text, we will also be going deeper with additional lecture material and some outside readings tailored for advanced CS undergraduates and beginning graduate students.

We will have periodic homework assignments, in-class quizzes comprising short answer problems, and perhaps a few longer homework problems.

Project: The capstone project for the course will be a semester-long research project, culminating in a writeup and a presentation to the class, which will take the form of a poster and/or a demo at a class-wide poster+demo session. The topic of the research project will be for students to conduct a study of a computational aspect of an e-commerce firm or of consumer behavior with respect to an e-commerce marketplace. Students may work in teams of two or three, with the expected output of the teams to be commensurately larger. Suggested project topics and project deadlines will be announced after the first few weeks of the course, with regular milestones throughout the semester. I will expect students in this class to take the project very seriously and there will be regular interaction with the instructor outside of class to work on the projects --- ideally, several of the best projects in the class will eventually continue beyond the class, in a direction towards publication or commercialization.

Research studies may take a variety of forms, depending on students' interests and aptitudes. The most typical project will be to conduct and write up a research study that is a quantitative, i.e., data-driven, analysis of a computational aspect of an e-commerce firm or of consumer behavior with respect to a networked marketplace. We will discuss several examples of these a few weeks into the semester. An ambitious, but reasonable goal for CS graduate students, would be to initiate a line of work with the potential to further develop as a publishable paper in the experimental track of the ACM Symposium on Economics and Computation, or to develop into a Masters thesis or dissertation chapter. Work will be graded based both on the effort demonstrated in the pilot study and on the promise of the proposed future work.

A second option is to design and write up an app, or other software system, that addresses a challenging direction in the general space of networked platforms. Work will again be graded based both on the demonstrated output and in the promise of the proposed future work, using grading at Hackathons as a barometer.

A third (and perhaps the most difficult) option is to develop a business plan to tackle a problem in this space, formatted both as a writeup and as a presentation pitch deck for seed funding in the $50K range (which will also be presented as a poster at the poster session). Work will be graded based on the quality of the pitch from the perspective of an investor, using competitiveness at a student business plan competition as a barometer.

If a team has an alternative project idea in mind that they believe is in scope, they should feel free to pitch it as a potential project direction at the appropriate early milestone in the class.
Course Topics
Course Schedule (as it evolves). Handouts and lecture slides are available on Piazza.