High School Dating (Bearman, Moody, and Stovel, 2004) (Image by Mark Newman)

Corporate E-Mail Communication (Adamic and Adar, 2005)

Note: This is not the current semester's course Web page. For current course information, handouts, and homework assignments, please visit the present semester's version of the course.

A course on how the social, technological, and natural worlds are connected, and how the study of networks sheds light on these connections. Topics include: how opinions, fads, and political movements spread through society; the robustness and fragility of food webs and financial markets; and the technology, economics, and politics of Web information and on-line communities.

The course is designed at the introductory undergraduate level with no formal prerequisites; it satisfies the Arts & Sciences Social and Behavioral Analysis (SBA) distribution and the Engineering Liberal Studies (SBA group) distribution. (See also the poster announcing the course.)

This is the fourth time the course is being offered; the home pages for the Spring 2007, Spring 2008, and Spring 2009 versions of the course are on-line as well.

See below for more information, including the class blog, the outline of topics, the schedule of office hours, and the CMS site (which you can log into using this CMS link).

Course Staff

• Instructors:
  • David Easley, 404 Uris Hall.
  • Jon Kleinberg, 5134 Upson Hall.
• Course Staff:
  • Vladimir Barash, email: vdb5.
  • Ram Dubey, email: rsd28.
  • Alex Ainslie, email: ana22.
  • Jacob Bank, email: jeb369.
  • Burak Bekdemir, email: ab465.
  • Eduard Dogaru, email: ed265.
  • Ken Ferguson, email: krf39.
  • Christie Gibson, email: ceg47.
  • Fahad Karim, email: fk66.
  • Sameer Nurmohamed, email: sfn4.
  • Ozgur Yonter, email: oy32.

Class Blog

There is a class weblog that we will be maintaining as part of the course, and posting to the blog will be part of the graded coursework, as described in the accompanying handout. The blog is hosted at Cornell, as part of the Expert Voices Gateway of the National Science Digital Library.

Information about the mechanics of posting can be found in the opening blog post.

CMS Site

At the CMS site, you can log in with your Cornell NetID to find information about your course grades and also to upload solutions to homework.

This semester, solutions to all problem sets, as well as the final paper, must be submitted through the CMS site, by the start of class on the days they are due. This means that you should write these up in an electronic format (Word files, PDF files, and most other formats can be uploaded to CMS). Also, you should check the CMS site at the start of the semester to make sure that you are able to log in. Please let us know if you experience any difficulties with this.

Outline of Topics

(1) Graph Theory and Social Networks

The course begins with a discussion of some of the general properties of networks. It develops this through examples from social network analysis, including the famous ``strength of weak ties'' hypothesis in sociology, and it connects these themes to recent large-scale empirical studies of on-line social networks.

Readings (Jan 25 - Feb 1)

• Chapters 1-3 and Chapter 5 of the Networks book draft.

Optional further reading:

• Chapter 2 of The Tipping Point, Sections 1-5. (The remainder of the chapter is useful as well, but less central to the content of the lectures.)
• Mark Granovetter. The strength of weak ties. American Journal of Sociology, 78:1360--1380, 1973.
  (This is Granovetter's original paper describing his work covered in Chapter 3 of the Networks book.)

(2) Game Theory

Since most network studies require us to consider not only the structure of a network but also the behavior of the agents that inhabit it, a second important set of techniques comes from game theory. This too is introduced in the context of examples, including the design of auctions and some ``paradoxical'' phenomena surrounding network traffic congestion.

Readings (Feb 3 - Feb 10)

• Chapters 6, 8, and 9 of the Networks book draft. (We will cover Chapter 7 later in the semester.)

Optional further reading:

• Ignacio Palacios-Huerta. Professionals Play Minimax. Review of Economic Studies, 70(2003), pp. 395-415,
  (This is the paper that studies penalty kicks in soccer, as discussed in Section 6.8.)
• Chapter 1 of Micromotives and Macrobehavior.

(3) Markets and Strategic Interaction on Networks

The interactions among participants in a market can naturally be viewed as a phenomenon taking place in a network, and in fact network models provide valuable insights into how an individual's position in the network structure can translate into economic outcomes. This provides a natural illustration of how graph theory and game theory can come together in the development of models for network behavior. Our discussion in this part of the course also builds on a large body of sociological work using human-subject experiments to study negotiation and power in networked settings.

Readings (Feb 12 - Mar 1)

• Chapters 10-12 of the Networks book draft.

(4) Information Networks and the World-Wide Web

The Internet and the Web of course are central to the argument that computing and information is becoming increasingly networked. Building on the earlier course topics, we describe why it is useful to model the Web as a network, discussing how search engines make use of link information for ranking, how they use ideas related to power and centrality in social networks, and how they have implemented network-based matching markets for sellling advertising.

Readings (Mar 3 - Mar 19)

• Chapters 13-15 of the Networks book draft.

(5) Network Dynamics: Population Models

Networks are powerful conduits for the flow of information, opinions, beliefs, innovations, and technologies. We begin by considering how these processes operate at the level of populations, when we can't necessarily observe the network itself, but only its effects on aggregate behavior. As part of this, we consider phenomena including information cascades, "tipping points" in the success of products with network effects, and the distribution of popularity.

Readings (Mar 29 - Apr 16)

• Chapter 7, Chapters 16-18, and Chapter 22 of the Networks book draft.

Optional further reading:

• Introduction and Chapters 1 and 6 of The Tipping Point.
• Chapter 3 of Micromotives and Macrobehavior.

(6) Network Dynamics: Structural Models

We continue our exploration of how things flow through networks, focusing on what we can learn from details of the network structure itself. Here we study how both behaviors and diseases can spread through a social network, and also some of the network phenomena that underpin the "six degrees of separation" effect.

Readings (Apr 19 - Apr 30)

• Chapters 19-21 of the Networks book draft.

Optional further reading:

• Michael Suk-Young Chwe. Structure and Strategy in Collective Action. American Journal of Sociology 105(1999), pp. 127--156.

(7) Institutions and Aggregate Behavior

Finally, a perspective based on networks can provide novel insights into the structure of social institutions, and into basic policy questions in many areas. We illustrate this theme with examples based on markets, voting theory, and property rights.

Readings (May 3 - May 7)

• Chapters 23-24 of the Networks book draft.

Books

We will be using a pre-publication draft of the book Networks, Crowds, and Markets, which we've developed while teaching this course over the past several years. A complete draft is on-line at the Web page for the book, and a printed version of it is also available through the Campus Store (for a charge per page to cover the printing costs).

There are also two optional books for the course:

• The Tipping Point: How Little Things Can Make a Big Difference. Malcolm Gladwell, Little, Brown and Company, 2002.
• Micromotives and Macrobehavior. Thomas C. Schelling, W. W. Nor ton and Company, 2006.

These two optional books contain material that supplements and expands on some of the course topics.

Office Hours

• Mon 12:30 - 1:30: Alex Ainslie, 328B Upson
• Mon 2:00 - 3:00: Sameer Nurmohamed, 328B Upson
• Mon 3:00 - 4:00: Jon Kleinberg, 5134 Upson
• Mon 4:00 - 5:00: Vlad Barash, 368 Uris
• Tue 11:00 - 12:00: Ken Ferguson, 244 Clark
• Tue 1:15 - 2:15: Jon Kleinberg, 5134 Upson
• Tue 3:00 - 4:00: Ozgur Yonter, 328B Upson
• Wed 12:30 - 1:30: Fahad Karim, 328A Upson
• Wed 1:30 - 2:30: Burak Bekdemir, 328A Upson
• Wed 2:00 - 4:00: David Easley, 404 Uris
• Thu 12:00 - 1:00: Jacob Bank, 328A Upson
• Thu 1:00 - 2:00: Christie Gibson, 328A Upson
• Thu 3:00 - 4:00: Eduard Dogaru, 328A Upson
• Fri 9:30 - 10:30: Ram Dubey, 408 Uris

Prerequisites

Almost no knowledge of specific mathematical content is assumed, other than some basic probability (random variables, expectation, independence, and conditional probability), which we will briefly review when it first arises.

However, the main goal of the course will be to build mathematical models of the processes that take place in networks. As such, students will be expected to interpret and work with mathematical models as they come up the course; at the same time, students should also think about how to relate these models to phenomena at a qualitative level.

Coursework

• Midterm: Monday, March 8, in class.
• Final exam: Wed, May 12, 7:00 - 9:30 pm, Barton Hall.
• Approximately 6 problem sets. As described above, these must be submitted using the CMS site, by the start of class on the days they are due.
• A short (4-6 page) paper due the last week of class. The paper is designed to be an exploration of a topic related to the course, containing both a discussion of prior work, and some novel discussion or analysis of the topic. Like the problem sets, the final paper must be submitted using the CMS site.
• Class blog: As discussed above, there is a class weblog and each student should make two posts to it as part of the graded coursework. See the accompanying handout describing the format and schedule for blog posts. The opening blog post describes how to register for the blog and begin submitting posts.

Grades on homework, the paper, blog posts, the midterm, and the final will be weighted as follows:
• Midterm: 20%
• Final: 30%
• Homework: 20%
• Short Paper: 20%
• Blog Posts: 10%

Academic Integrity

You are expected to maintain the utmost level of academic integrity in the course. Any violation of the code of academic integrity will be penalized severely.

You are allowed to collaborate on the homework to the extent of formulating ideas as a group. However, you must write up the solutions to each problem set completely on your own, and understand what you are writing. You must also list the names of everyone that you discussed the problem set with.

Collaboration is not allowed on the other parts of the coursework.

Finally, plagiarism deserves special mention here. Including text from other sources in written assignments without quoting it and providing a proper citation constitutes plagiarism, and it is a serious form of academic misconduct. This includes cases in which no full sentence has been copied from the original source, but large amounts of text have been closely paraphrased without proper attribution. To get a better sense for what is allowed, it is highly recommended that you consult the guidelines maintained by Cornell on this topic. It is also worth noting that search engines have made plagiarism much easier to detect. This is a very serious issue; instances of plagiarism will very likely result in failing the course.