Final Exam: Tuesday, May 20 in our classroom, 1:30-3:30PM.

2/18 (Tuesday) - Upcoming:

  1. Please bring your laptops to class on Thursday so we can explore the "Facebook network graph."
  2. Additionally, check out this paper on romantic partnerships and socialties. This is for you to discuss in class next Tuesday.

1/28 (Tuesday) - As per instructions given in class, please complete the following two items by Thursday (1/30):

  1. Sign up for Piazza. You should have received an invitation from Piazza to your umd email to join the class. If not, please sign up manually (instructions given below.)
  2. We will split you into groups of 3 for doing projects in this class. Please send an email to all 3 TA's stating either
    1. your desired group (1 email per group will suffice), or
    2. that you have no preferred group (we will assign you).
    Note that the email address given for Alexa in class was incorrect, please use the correct address above.


We will be using Piazza for this class. Please sign up for the class as follows:

  1. Go to and click the "Students get Started" button to Search for Schools
  2. Enter University of Maryland (
  3. Enter CMSC 287: Network Science and Networked Information... (the rest should autocomplete)
  4. Click the "Join as Student" bubble and then click the "Join Classes" button below.
  5. Enter your school email address (, and a new password (or old password if you have used Piazza before)


Project 1 Due by the start of class on Feb 13, 2014. Piazza post with the project description.
Project 2 Due by 12 noon on March 5, 2014. Project description.
Project 3 Due by 12 noon on March 12, 2014. Project description.
Project 4 Due by 11:59PM on Thursday, April 3rd. Project description.
Project 5 Due by 11:59PM on Monday, April 21st. Project description.
Project 6: Extra-Credit Due by 11:59PM on Monday, May 5th. Project description.
Final Project Due by 11:59PM on Friday, May 9th. Project description.


The following is a tentative schedule for the semester.

Week 1 Broad discussion of networks of different types, their genesis (including the ideas of visionaries such as Vannevar Bush). Mathematical foundations including basic graph theory and probability; overview of class. Start forming groups. Lecture 1 Lecture 2
Week 2 More graph theory. Granovetter's thesis; strong and weak ties in networks and connections to referrals in social networks; triadic closure and the strength of weak ties; bridges and local bridges. Lecture 3 Lecture 4
Week 3 Large-scale experiments about strong and weak ties; embeddedness; social capital and structural holes. Start homophily, and a mathematical model to measure it. (One class canceled due to the university's snow-related shutdown.) Lecture 5
Week 4 Selection, social influence, and social contagion; affiliation networks; models for various types of closure; networks with “positive” and “negative” ties - structural balance and applications in geopolitical ties; a balance theorem. Lecture 6 Lecture 7 Chapter 4 Chapter 5
Week 5 Embeddedness vs. "dispersion": the work of Backstrom and Kleinberg. Weaker forms of structural balance. Mid-semester feedback on the class. Lecture 8
Week 6 A more detailed analysis of dispersion; start cascading behavior. Chapter 19
Week 7 More on Cascading behavior. Mid-term in class on Thursday. Chapter 16
Week 8 More information diffusion in networks; brief history of information retrieval, and Kleinberg's hubs-and-authorities approach.
Week 9 Game theory in detail.
Week 10 Game theory, auctions, and sponsored-search advertising. Chapter 6
Week 11 Finish Web advertising. Models for social-contact networks and the percolation of infectious diseases; connections to epidemiology, quarantining, and vaccination. Brief discussion of collective intelligence (and its amplification), systems such as InnoCentive, and citizen science.
Student presentations, a review of the future of the networks including personalized medicine and mobile health, and summary.


10% Attendance, class participation, and team-work. Students will need written permission if they are absent for more than two classes for non-essential reasons (essential reasons include documented health, religious holidays, and family emergencies).
30% Projects done throughout the semester.
10% Final class presentation on each team’s projects done throughout the semester.
10% Mid-term exam.
30% Comprehensive final exam.
10% Final term research paper (by each team) on:
  1. the analysis of existing networks, or
  2. a detailed proposal on developing new social-network-based businesses or applications (network-based lending for educational loans is an illustrative example.)

Suggested Readings