MSc Social Network Analysis

• Research design
• Data collection (whole networks)
• Data collection (ego networks)
• Archival data
• Visualization in iGraph and SNA, layout algorithms.
• Visualization in other packages Eg Visone/ Gephi Missing data
• Negative ties
• Large networks
• Network measurement theory

The main aim of the course is to provide a solid understanding of various types of network data. Understanding the sources of such data, their properties and limitations. In addition to be able to gather and manipulate both on line and off line data for later analysis. The course provides a set of fundamental skills including data visualization that are required for the more dedicated units where the analysis of network data is the primary goal.

• Design and develop network studies and intervention that can be used in private and public sectors.
• Understand the variety of network data, ie. egonets, whole networks, multilevel networks, longitudinal networks, multimode networks.
• Assess the feasibility and applicability of a wide range of analytical techniques to social network data
• Collect social network data in online and offline contexts, selecting the right data collection tools and assessing the validity and reliability of the data collection.
• Produce cutting edge data visualization in a meaningful way.

Each week contains a one hour lecture followed by a 2 hour computer laboratory session.

3000 word report (100%)