Digital Methods and Transformation – Applied Social Network Analysis

About

Digital technologies are increasingly permeating the way we work, live, and think. A crucial aspect of the digital transformation lies in the ever increasing amount of data that is being produced about individuals and organizations alike. Big data is the keyword to characterize the unprecedented volume, velocity, and variety of data being produced in the digital age. Increasingly, organizations are harnessing the power of big data through data mining and analytics. Gaining insights from big data can be challenging and requires specialized knowledge, also in data and network visualization. This course will equip students with a set of analysis techniques to make sense of data in a visual way. A focus will be on social network analysis to study relational data, identify influential nodes in a network, and distinguish communities.

Course leader

Christian Fieseler and Christoph Lutz

Target group

Master students.

Eligible applicants must have a completed degree comparable to a bachelor’s degree. Students are expected to have taken classes in statistics and have working knowledge of MS Excel and SPSS. We expect students to have a solid grasp of the English language as well as a strong interest in the issues at hand, and to actively participate in class.

Course aim

After taking this summer school course, students will

understand digital transformation better
be equipped with the concepts to analyse relational dynamics of social and digital media effectively
have the methodological tools at hand to analyse social networks from a range of data
be able to interpret network visualisations and articles using social network analysis appropriately

Fee info