Course Information
- Location: Software Engineering Building, 102
- Time: Sundays, 17:00 - 20:00
Course Instructor:
Course Goals and Short Syllabus:
Today we cannot imagine our life without social networks. The interest in analyzing social networks, their structure, predicting expected behavior of the users in social networks increased in the past years.
This course will focus on social networks and especially online social networks, bringing together both algorithms (from "classic" to recent state-of-the-art) and applications for these networks.
The course will involve both theoretical parts (such as formal definition of social network, measurements in social networks, network formation, community detection algorithms and more) and practical parts (including hands-on programming using Python and libraries such as NetworkX).
In addition to covering fundamental issues in social networks, we will focus on practical real world tasks, including the trends from the last years.
For practice, we will use publically available datasets of social networks and demonstrate solution of real life challenges.
Course Format:
Each class will be a 3 hours lecture which will include both theoretical and practical parts.
Homework - 3 HW assigments during the semester (submission in pairs) - 15% of the final grade
Final exam - 85% of the final grade
Exam - Moed A: 06.07.2020
Exam - Moed B: 09.08.2020
Requirements:
Homework
Course Schedule
| # |
Date |
Title |
Material |
Note |
| 1 |
08.03.2020 |
Introduction to Social Networks |
Lecture [pdf], Recitation [ipynb] |
|
| 2 |
15.03.2020 |
Random Graphs, Centrality |
Lecture [pdf], Recitation [ipynb] |
|
| 3 |
22.03.2020 |
Signed Networks, Structural Balance |
Lecture [pdf], Recitation [ipynb] |
|
| 4 |
29.03.2020 |
Communities |
Lecture [pdf], Recitation [pdf] |
|
| 5 |
19.04.2020 |
Detection of communities |
Lecture [pdf], Recitation [ipynb] |
|
| 6 |
26.04.2020 |
Application: Fraud, Crime and Terrorism prevention |
Lecture [pdf] |
|
| 7 |
03.05.2020 |
Influence Maximization |
Lecture [pdf], Recitation [ipynb] |
|
| 8 |
10.05.2020 |
Social Learning |
Lecture [pdf], Recitation [ipynb] |
|
| 9 |
17.05.2020 |
Link Prediction |
Lecture [pdf], Recitation [ipynb] |
|
| 10 |
24.05.2020 |
News Feed, Ads and Data Leakage |
Lecture [pdf] |
|
| 11 |
31.05.2020 |
Working with Large Scale Networks |
Lecture [pdf] |
|
| 12 |
07.06.2020 |
Course Summary |
Lecture [pdf] |
|
| 13 |
14.06.2020 |
Exam Preparation |
Lecture [pdf] |
|
Previous exams
