Social Media Analytics

The course will cover techniques and algorithms to analyze the structure of large social networks, and to identify their main properties. We start by introducing the basic concepts of social media analytics. Next, the course will delve into studying the main measures and models used for social media networks and techniques applied to identify communities. Then, the course will cover social media application topics including, diffusion/influence in social networks, crowdsourcing in the web, social recommendation and location-based social media.
 

Learning Outcomes: 

On successful completion of this course, you will be able to:

  • Analyze a social media network and identity its main properties
  • Understand how to apply clustering techniques to detect communities
  • Apply matrix factorization/decomposition techniques on social media networks
  • How to boost recommendation systems using user social networks
  • Identify the main characteristics of human mobility in social networks and its applications
     
Type: 
Course
Semester: 
S2019
ECTS: 
5
Tracks: 
Site: 
F
Code: 
63091
Language: 
english
Period: 
weekly
Schedule: 
Thursday: 9:15 - 12:00
Location: 
UniFR, PER21
Room: 
C230
Evaluation type: 
written exam
Comment: 

First Lecture
The first lecture will take place on Thursday, 21.02.2019 at 09:15 in UniFR, PER21, room C230.

ILIAS
The course page in ILIAS can be found at https://ilias.unibe.ch/goto_ilias3_unibe_crs_1340288.html.