Single-Course English 10 ECTS

Social graphs and interactions

Overall Course Objectives

The overall objective of the course is to make students able to access and analyze user generated data and text – as well as analyze and model social relations using network theory.

Learning Objectives

  • Explore web APIs for data collection.
  • Apply a high level programming language (e.g. Python) to utilize such APIs for data acquisition.
  • Apply natural language processing to represent statistical structures in text and analyze the content.
  • Apply and discuss the main strategies for detecting sentiment in media (e.g. text, music, images, etc).
  • Apply standard algorithms to recommend media (text, audio, video) according to user preferences and user context (friends, mood, location, etc).
  • Assess basic metrics for complex networks, and model social relations based on network analysis.
  • Implement software for detecting communities in social networks and analyze the communities using network metrics
  • Quantify relations in social networks to analyze their dynamics, using measures from complex network theory.

Course Content

The course is based on analyzing data from online social networks (e.g. Twitter, Wikipedia, and Facebook), as well as working with quantitative text analysis. The course is structured around short lectures combined with exercises, as well as a high degree of independent project work.

Recommended prerequisites

02100/02101, The course involves work with high level programming languages (e.g. Python), so practical programming experience is recommended (e.g. in Python/Java/JavaScript/C/C++)

Teaching Method

Lectures and group work with projects.



It is recommended to bring your own laptop computer to carry out exercises in the course.

See course in the course database.





13 weeks




DTU Lyngby Campus

Course code 02805
Course type Candidate
Semester start Week 35
Semester end Week 48
Days Wed 8-17

15.000,00 DKK