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Workshop on Social Network Analysis Theory, Methods and Applications

Tuesday, February 8, 2022 to Wednesday, March 16, 2022

Event Details

We will be running an online introduction course for Social Network Analysis via a series of 12 workshops over a 6-week period (8 Feb – 18 Mar).  There will be 2 x 3-hour workshops each week where we will introduce topics to you, then apply that knowledge straight away through applied social network exercises.  We will introduce you to and guide you through the use of social network software.

You will learn how to conduct social network research, moving from the fundamentals of networks to an introduction to cutting-edge statistical network models. A general knowledge of statistics is assumed (e.g., correlation, logistic regression). You will require your own PC laptop (or Mac with Windows installed – Mac OS is not supported). Software will be provided.

Here is the course registration link:

Network Fundamentals
• What is distinctive about social network research?
• Network data: Representations and formats
• Qualitative versus quantitative data collection
• Primary versus secondary data sources
• Ethics for network research
• Organisational network methods
• Data entry, data processing and management
• VPNet software for visualisation of networks

Key Concepts & Descriptive SNA
• The building blocks of networks: density; reciprocity; degree; connectivity; centrality; clustering; and preferential attachment (popularity)
• Social Selection vs Social Influence
• Multiplex and bipartite networks
• Introductory approaches to statistical inference
• Introduction to Exponential Random Graph Models (ERGMs)
• Formation of network structure
• MPNet software for network models

Network Evaluation
• Network effectiveness
• Network problem solving

Standard: AUD$3,000 (including GST)
Students: AUD$1,500 (including GST)

For more information, please contact Peng Wang:

Please do not hesitate to contact me if I can be of any further assistance / provide further information on this course.