Social Network Analysis (SNA) for BigData

State: completed by Robin Stohler

This thesis will focus on the possibilities of calculating Social Network Analysis (SNA) metrics for large data sets. The goal is to transfer large log files into different graphs with millions of nodes which will then be used to calculate SNA metrics.

The size of the original data set and the resulting graphs will be too large to process efficiently on a singel machine. Therefore, BigData approaches like Hadoop have to be investigated and algrothms found or developed that can leverage BigData tools for the calculation of SNA metrics.

Final Report

40% Design, 40% Implementation, 20% Documentation
required: Programming skills, optional: Matlab, Hadoop, SNA

Supervisors: Andri Lareida

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