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MO412 / MC908 - Network Science
Instructor: Joao Meidanis, meidanis at unicamp dot br
Mondays and Wednesdays, 7-9pm, online. Check Graduate Schedule
Second Semester, 2020
Overview
This is an introductory course on Network Science. We will closely follow Barabási's book, a classic in the field.
We will follow an online model of education. The instructor will record pieces of lectures, based on slides, and make them available to students beforehand, together with the slides in PDF. Students can watch these pieces at their own convenience. During class, we will have a videoconference for comments, questions, and suggestions, but attendance will not be required. However, we invite all students to join our first videoconference on Sept. 16th for general information and course outline.
For their own presentations, students will follow a similar course of action. They will produce videos with their presentations, based on the guidelines, and make them available to the instructor. Assingments will be handed-out via our Google Classroom. Students may hand-in their assignments via Classroom also or by a private email to the instructor.
Office hours
By appointment only.
Program and Schedule
| MO412A | Graph Algs. / Network Sci. | 2nd. Term | |
| MC908A | Special Topics: Comp. Theory | 2020 | |
| Instructor: João Meidanis | |||
| PRELIMINARY SCHEDULE | Last Modified 2020-10-06 | ||
| Mo/We | Date | Topic | Book Chapter |
| Mon | 09/14 | ||
| Wed | 09/16 | Course Outline | |
| Mon | 09/21 | Introduction (slides) | 1 (video) |
| Wed | 09/23 | Graph Theory (slides) | 2 (video) |
| Mon | 09/28 | Graph Theory (slides) | 2 (video) |
| Wed | 09/30 | Graph Theory (slides) | 2 (video1) (video2) |
| Mon | 10/05 | Random Networks (slides) | 3 (video1) (video2) |
| Wed | 10/07 | Random Networks (slides3) (slides4) | 3 (video3) (video3) |
| Mon | 10/12 | Holiday: no class | Holiday: no class |
| Wed | 10/14 | The Scale-Free Property (slides) | 4 (video1) (video2) |
| Mon | 10/19 | The Scale-Free Property | 4 (video3) (video4) |
| Wed | 10/21 | The Barabási-Albert Model (slides) | 5 (video) |
| Mon | 10/26 | The Barabási-Albert Model (slides) | 5 (video) |
| Wed | 10/28 | Holiday: no class | Holiday: no class |
| Mon | 11/02 | Holiday: no class | Holiday: no class |
| Wed | 11/04 | Hands-on Class (colab) | Gephi, Python (video1 video2) |
| Mon | 11/09 | Preliminary Project Presentations | Final Project (40%) |
| Wed | 11/11 | Evolving Networks (slides) | 6 (video) |
| Mon | 11/16 | Evolving Networks (sl.); Assignmt. 2 | 6 (video), Class Network (15%) |
| Mon | 11/16 | Last day for MO412 drop requests | |
| Wed | 11/18 | Degree Correlations (slides) | 7 (video) |
| Mon | 11/23 | Degree Correlations | 7 (video) |
| Wed | 11/25 | Collect Assignment 2 | Class Network (15%) |
| Mon | 11/30 | Network Robustness (slides) | 8 (video) |
| Wed | 12/02 | Network Robustness (slides) | 8 (video) |
| Mon | 12/07 | Holiday: no class | Holiday: no class |
| Wed | 12/09 | Hand-out Assignment 3 | Wikipedia Page (15%) |
| Fri | 12/11 | Last day for enrollment suspension requests | |
| Mon | 12/14 | Communities (slides) | 9 (video) |
| Wed | 12/16 | Communities (slides) | 9 (video) |
| Mon | 12/21 | Spreading Phenomena (slides) | 10 (video) |
| Wed | 12/23 | Spreading Phenomena (slides) | 10 (video) |
| Mon | 12/28 | Holiday: no class | Holiday: no class |
| Wed | 12/30 | Holiday: no class | Holiday: no class |
| Mon | 01/04 | Spreading Phenomena (slides) | 10 (video) |
| Wed | 01/06 | Research Project Discussions | |
| Mon | 01/11 | Collect Assignment 3 | Wikipedia Page (15%) |
| Wed | 01/13 | Final Project Presentations | Final Project (40%) |
| Mon | 01/18 | ||
| Wed | 01/20 | Exam (undergraduates only) |
Grading
Grading will be based on a number of Assignments and a Final Project. The Assignments are individual, but the Final Project is to be carried out by a group of 2 students, preferably with different backgrounds. If the number of students in the class is odd, we will allow one group with 3 members. In the Final Project, the group will select a network of interest, map it out, and analyze it.
The Assignments are of three different types. The first type consists in solving homework problems assigned weekly by the instructor. The second type consists in analyzing the class network, which will be given to all students at an appropriate time during the course. The last type of assignment consists of writing a Wikipedia page about a network-related topic. The page must not exist yet.
For the Final Project, the groups must present their work as a 10-minute presentation on video, describing the data, how it was collected, several measures about the network, and insights gained by doing the analysis. The video presentation must begin by stating the title, name of group members, their program, and the date.
There will be midterm Preliminary Project Presentations to help groups refine their plans. For these, groups must prepare 5-minute presentations, based on no more than 5 slides. Further guidelines about the Assignments / Final Project will be given during the course.
Each type of assignment will give rise to a numeric grade in the range 0 to 10. The contributions of each type to the final grade are as follows:
| Type 1 (Homework) | 30% |
| Type 2 (Class Network) | 15% |
| Type 3 (Wikipedia) | 15% |
| Final Project | 40% |
Numeric grades will be converted to letter grades accorging to the following scheme:
| 8.5 to 10 | A |
| 7 to 8.5 | B |
| 5 to 7 | C |
| 0 to 5 | D |
Late penalties
For any of the Assignments, there will be penalties for late work. People who do not hand in their solutions on time will incur a late penalty of 20% of the grade per day, computed proportionally with the granularity of 1 minute. So you are 1 day late your penalty is 20%; 2 days late, 40%; 1 hour late, 0.833%; and so on.
Fraud
Any attempt at fraud in this course will entail final grade equal to zero for all involved, with possible additional sanctions, as deemed necessary by the University administration.
References
Network Science. Albert-László Barabási. Cambridge University Press, 2016.
Introduction to Algorithms, 3rd Edition. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein. The MIT Press, 2009.
Algorithms, 4th Edition. Robert Sedgewick, Kevin Wayne. Addison-Wesley Professional, 2011.