CAS CS 599B2 - Fall 2025 - Networks and Markets: Theory and Applications

Course Overview: The concept of a network has expanded beyond interconnected machines to encompass diverse applications emphasizing connectedness. Biological networks, social networks, online advertising networks, and networks involving hyperlinks are all examples of domains which now apply the theory and practice of network science. In parallel, online markets have emerged as key facilitators of commercial activity, from early platforms like eBay with online auctions to modern markets such as pay-per-click advertising, prediction markets, and two-sided platforms like Uber and Airbnb. These application domains draw deeply on established methodologies that are familiar to computer scientists, notably graph theory and algorithms. However, they also build on theoretical foundations that are less familiar to most computer scientists, such as auction design, mechanism design, and the theory of matching markets. Finally, many modern technologies integrate both networks and markets, such as information networks and recommender systems.

In this class, we will build upon the 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.

Prerequisites: This course is designed for declared CS and DS majors who are fulfilling 400-level electives. For CS students: CS 112, CS 131, and some knowledge of probability and statistics is required. CS 330 or equivalent is suggested as a co-requisite. For DS students: DS210, DS122 is required. DS320 is suggested as a co-requisite. While students' backgrounds will vary, it is expected that students are nearing completion of an undergraduate CS or DS major.

Class meeting times: Tues/Thurs 3:30-5, CDS 701.

I expect students to be in 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. Class time will regularly feature lightning talks from students to kick off discussions.

Instructor:  Prof. John W. Byers
Email: byers @ cs . bu . edu [preferred]
Office Hours (Fall 2025): TBD.

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 (very preliminary list):

Communications:

We will be using Piazza for all discussions outside of class. We will also use Piazza to post announcements, homework assignments, etc. 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.

The link for our class page is TBD.

AI Policy: We will be following the CDS GAIA policy in this course.


Course Requirements and Grading: There will be four 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.

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, held online in LfA style as best we can manage. 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. 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 will be made available on Piazza.