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


Corporate EMail 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.
Networks
Economics 2040 / Sociology 2090 / Computer Science 2850 / Information Science 2040
Cornell University, Fall 2010
MonWedFri 11:1512:05
The class meets in Statler Auditorium (Mon/Wed) and Ives 305 (Fri)
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 online 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.)
See below for more information, including the
class blog,
the outline of topics,
and the CMS site
(which you can log into using this
CMS link).
Course Staff

Instructors:

Course Staff:
 Max Mihm, email: mam293.
 Lu Wang, email: lw375.
 Jacob Bank, email: jeb369.
 Burak Bekdemir, email: ab465.
 Tim Bosworth, email: tbb33.
 Michael Brancato, email: mtb84.
 Christine Chen, email: ccc225.
 Karl Eichorn, email: kae55.
 Fahad Karim, email: fk66.
 Amitha Kurmala, email: ark77.
Class Blog
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.
Books
We will be using the book
Networks, Crowds, and Markets (Cambridge University Press, 2010),
which we wrote while teaching this course over the past several years.
A complete draft is online at the
Web page for the book,
and the published version is for sale at the Campus Store.
Outline of Topics
(1) Graph Theory and Social Networks
(2) Game Theory
(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 humansubject
experiments to study negotiation and power in networked settings.
Reading
(4) Information Networks and the WorldWide 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 networkbased matching markets for
sellling advertising.
Reading
(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.
Reading
 Chapter 7, Chapters 1618, and Chapter 22.
(6) Network Dynamics: Structural Models
(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.
Reading
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
 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 (46 page) paper. 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.
More information about the paper will given in a handout later
in the semester.
 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.