Internet analytics
COM-308
Media
Internet Analytics is the collection, modeling, and analysis of user data in large-scale online services, such as social networking, e-commerce, search, and advertisement. In this class, we explore a number of key functions of such online services that have become ubiquitous over the last couple of years. Specifically, we look at social & information networks, recommender systems, clustering and community detection, dimensionality reduction, stream computing, and online ad auctions.
The course is taught by Prof. Matthias Grossglauser and a team of teaching assistants.
The course is combination of theoretical materials and weekly laboratory sessions, where we explore several large-scale datasets from the real world.
In this course you have the great opportunity to work with a dedicated Spark infrastructure.
- Please choose your group for the Internet Analytics labs. Deadline: at start of Lab 2 (Group choice)
- Announcements (Forum)
Lecture 1
Course introduction and overview
Lab 1 (note: starts at 16h15)
The objectives of the next 2 lab sessions are the following:
- Familiarize yourself with our lab infrastructure
- Follow the tutorials on
- Python
- Data Science
- Spark
- Networks
- Lecture 01: slides (File)
- ix-lab1-intro handout (File)
- ix-lab1-intro-solution-2025.ipynb (File)
- ix-lab1-intro-files-2025 (File)
Lecture 2
Social and Information Networks 1: Structure
Lab 1 (continued: starts at 16h15)
Lecture 3
Social and Information Networks 2: Evolution
- Lecture 03: slides (File)
- Lecture 03: video (URL)
- ix-lab2-handout-2025 (File)
- ix-lab2-files-2025 (File)
No class this week
Lecture 4
Social and Information Networks 2: Processes
Lecture 5
Social and Information Networks 4: Ranking
Lecture 6
Dimensionality Reduction
Graded Lab 2 deadline: Thursday, April 3, 4:00 pm
Lab 3 start, Thursday, April 3, 4:15 pm
- Lecture 06: slides (File)
- Lecture 06: video (URL)
- lab3-handout (File)
- Homework 3 (File)
- Homework 3: solutions (File)
- ix-lab3-recsys-files-2025 (File)
Lecture 7
Recommender Systems 1
Lecture 8
Lecture 9
Text Models 1
Lecture 10
Text Models 2
- Lecture 10: slides (File)
- Lecture 10: video (URL)
- Homework 5 (File)
- Homework 5: solutions (File)
- ix-lab4-text-handout-2025 (File)
- ix-lab4-text-files-2025 (File)
Lecture 11
Lecture 12
Lecture 13
Ad Auctions
I am unfortunately sick and need to cancel today's lecture -- sorry for the inconvenience!As I had mentioned last week, today's lecture is not covered in the final exam. If you are interested in the topic, I encourage you to watch the lecture video below.
I will publish practice exams from past years later today to help you prepare.
- Lecture 13: slides (File)
- Lecture 13: video (URL)
- Final practice exam (2020) with solutions (File)
- Final practice exam (2024) (File)
- Final practice exam (2024) with solutions (File)
Lecture 13
Ad Auctions
Graded Lab 4 deadline: Wednesday, June 7, 10:00 am
Exam
The exam starts at 9:15 am on Tuesday 17th of June.
Students with names from A to Kh (plus Stefan Peters) are in room BS160.
Students with names from Ki to Z are in room BS170.
You can find your seat number in the pdfs below.
You are allowed to have all the material you want from the class, printed or handwritten (including your own notes).
You are not allowed to have any external material. You are not allowed to have electronic devices (also no calculator). Exams, homeworks and their solutions are allowed.