Applied Social Network Analysis using Advanced Data Mining

 

Richard Weber, 14 September to 18 September

Content

Social networks play an ever increasing role in our society. Facebook and Twitter are just two such internet sites where users can network. Many traditional business decisions will be influenced by social network analysis (SNA). Loan granting or marketing campaigns are just two examples. But also less traditional areas, such as e.g. investigation of organized crime, can benefit from this relatively new approach. This course first lays the foundation for social network analysis by introducing advanced data mining techniques. Then the main topics related to SNA will be introduced. Applications with real-world data from social networks using the respective software tools will conclude the course.  

Teaching Objectives

This course seeks to enhance participants’ ability to:

  • understand the potential of social network analysis (SNA) in different areas, such as e.g. business or organized crime,
  • select the adequate methods for network analysis,
  • analyze social networks using advanced data mining techniques,
  • propose decisions based on the respective network analyses. 

Prerequisites

  • Solid command of English.
  • Willingness to engage in preparatory readings of case studies and/or research papers.
  • Exchange and Erasmus students are cordially invited to apply for participation in this course

Due to the interactive teaching format, the number of participants is limited to 45.

Grading

The final grade will be composed as follows:

  • Option A: Colloquium & student presentation (weight: 50%) and written exam (60 minutes, weight: 50%)
  • Option B: Colloquium & student presentation (weight: 50%) and student paper (weight: 50%)
  • Option C: Colloquium & student presentation (weight: 50%) and oral exam (weight: 50%)
  • Option D: Colloquium & student presentation (weight: 100%)

All components specified for the respective option need to be passed in order to pass the module. The exact form of examination (A, B, C, or D) will be announced at the start of the course. Unless announced differently, Option A will apply.

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