Networks, Crowds and Markets

582675
4-6
Algorithms and machine learning
Advanced studies
We go together through the book David Easley and Jon Kleinberg: Networks, Crowds and Markets ¿ Reasoning about a Highly Connected World, Cambridge University Press, 2010. The book discusses social network analysis using methods from computer science and economics. The course is an advanced Computer Science course suitable for inclusion in the MSc degree in the sub-programmes Algorithms and Machine Learning, and Networking and Services. The language of the course is English. The course is passed by active participation in the course.
Year Semester Date Period Language In charge
2011 spring 14.03-20.05. 4-4 English Patrik Floréen

Lectures

Time Room Lecturer Date
Wed 16-18 C222 Patrik Floréen 14.03.2011-20.05.2011

Registration has ended on 24th of February!

Information for international students

Course during (the extended) Period IV 14.3.-20.5.2011, led by Patrik Floréen

Group division (explicitly agreed with the participants to publish this list on the web in this form): table.

The course is an advanced Computer Science course suitable for inclusion in the MSc degree in the sub-programmes Algorithms and Machine Learning, and Networking and Services. The language of the course is English.

The objective of the course is to go together through the new book “David Easley and Jon Kleinberg: Networks, Crowds and Markets – Reasoning about a Highly Connected World,” Cambridge University Press, 2010. The book, available online (click here!) discusses especially social network analysis using methods from computer science and economics: graph theory, game theory, auctions, voting. As the book is actually intended for undergraduates with different majors, most of the material in the book is actually very easy and verbose for a short advanced course; thus we will go through the book in a rapid manner concentrating on the more advanced material.

Advance knowledge required: Course “Data Structures” is in practice compulsory and additional courses in algorithmics and mathematics, such as “Design and Analysis of Algorithms” and “Probability Theory” are of benefit.

The course is passed by active participation in the course by solving exercises and taking lead roles in handling the book (see below). The course grade is a function of number of exercises solved moderated by the teacher’s appreciation of course activity.

The course consists of weekly sessions according to the following schema for each session (except the first session):

  • The part of the book for which exercises are now to be gone through is discussed among the participants: what was interesting, what was good/bad, pointers to interesting research questions.
  • Homework exercises are gone through, so that participants present their results (the homework needs to be solved in advance), with the person having the lead role for the corresponding part of the book presenting “model answers” if needed.
  • Then the person having the lead role for the next part of the book explains this part of the book by summarizing the content and main concepts/defintions, pointing towards more interesting parts of the material and passages of the book (at most some tens of pages) worth reading for everybody.
  • Finally, the person having the lead role for the next part of the book tells which exercises are to be solved for the next session.

In the first session, Patrik Floréen takes the lead role. The other lead roles are distributed during the first session. If there are many participants, there will be a split of roles between two persons for each part of the book. Due to Easter vacation, there will be an extra session agreed, so that there is a session both just before and just after Easter vacation. However, due to the exam week, there will be no session week 18. For 4 ECTS points, participation in sessions 1-6 are required, for 6 ECTS points, participation in sessions 1-9 are required.

The contents of the sessions are as follows:

  1. 16.3. (week 11) Introduction; arrangements on the course; presentation of Part I of the book (P. Floréen): slides, solutions to exercises
  2. 23.3. (week 12) Solving exercises (Part I); presentation of Chapters 6-7 of the book: slides, solutions to exercises
  3. 30.3. (week 13) Solving exercises (Ch 6-7); presentation of Chapters 8-9 of the book: slides, solutions to exercises
  4. 6.4. (week 14) Solving exercises (Ch 8-9); presentation of Part III of the book: slides, solutions to exercises
  5. 13.4. (week 15) Solving exercises (Part III); presentation of Part IV of the book: slides, solutions to exercises
  6. 20.4. (week 16) Solving exercises (Part IV); presentation of Part V of the book: slides (received 26.7.), solutions to exercises
  7. 27.4. (week 17) Solving exercises (Part V); presentation of Part VI of the book and presentation of Part VII of the book - long session. Part VI: slides, solutions to exercises; Part VII: : slides, solutions to exercises
  8. 18.5. (week 20) Solving exercises (Part VI and Part VII); final remarks

(The slides and solutions to exercises will come up in due time; the links do not work until then.)

Note that there is no exam in the course; thus there are no separate exams later on.

The grading of the course is based on the number of exercises solved. The minimum amount for passing the course (grade 1) is half of the exercises. The highest grade 5 is achieved with solving 5/6 of the exercises, and the other grades are linearly in between. In other words: 7/12 -> grade 2, 2/3 -> grade 3, 3/4 -> grade 4. With 4 exercises per session, there will be 32 execises for the 6 ECTS version of the course, giving the following table

16-18 exersises: 1

19-20 exercises: 2

21-23 exercises: 3

24-26 exercises: 4

27-32 exercises: 5

Particularly good or bad performances with regards to handling the lead role may increase or decrease the grade.