Social Media & Social Network Analysis II
level of course unit
second cycle, Master
Learning outcomes of course unit
The students will be in a position to apply models, methods and approaches of social network analysis (SNA) to concrete application scenarios for social media.
They will understand the possibilities of analyzing and modeling data from the (social) networks, and will be able to initiate and interpret analyses by means of SNA software tools.
prerequisites and co-requisites
In this course, following on from "Social Media and Social Network Analysis I", details will be covered of the usability of social network analysis (SNA), in particular the social media instruments/channels.
The students will become conversant with basic theoretical approaches (in particular statistical approaches and others supported by game theory), methods for collecting network data and various other analytical processes including the fundamentals for modeling these processes.
Here, data from the first course will be accessed and analyzed using software tools. On the basis of these activities the basic analytical possibilities in the social networks and possible conclusions will be discussed.
The questions how interactions in social networks like Linkedin, Facebook, Twitter, Google+ can be analyzed, visualized and used, and what conclusions are to be drawn from this, are central here.
At the same time, on the basis of relevant analyses, central elements for the development of (social media) strategies for applications in the company as well as on the consumer markets will be introduced.
recommended or required reading
- Easley, D. / Kleinberg, J. (2010): Networks, Crowds, and Markets - Reasoning about a Highly Connected World. Cambridge University Press
- Prell, C. (2012): Social Network Analysis. Sage
- Russel, M. (2011): Mining the Social Web - Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites. O'Reilly
assessment methods and criteria
project work, presentation
language of instruction
number of ECTS credits allocated
planned learning activities and teaching methods
Lecture, group work, presentation and task discussion
semester/trimester when the course unit is delivered
name of lecturer(s)
Mag. (FH) Thomas Meyer
year of study
recommended optional program components
course unit code
type of course unit
compulsory (integrated lecture)
mode of delivery