Social network analysis five-day course: Theory, method and application
|Date:||Monday 12 February – Friday 16 February 2018|
|Time:||9.30am – 4.30pm each day|
|Venue:||AGSE207, AGSE Building, Hawthorn Campus|
|Full-time PhD students:||$ 1,500.00|
|Swinburne staff:||$ 1,500.00|
|Swinburne PhDs:||$ 900.00|
Join this five-day intensive social network analysis (SNA) course.
Learn how to conduct social network research, moving from the fundamentals of networks to how to use cutting-edge statistical network models.
Some general statistical knowledge is assumed.
The couse will cover the following themes:
- Statistical Inference with network data
- Software for visualisation and analysis
- Representing network data: from basics to advanced
- Networks in action: Case studies
- Applying SNA
- One-on-one consultation times and group problem solving tasks
You will require your own PC laptop (or Mac with Windows installed).
The course includes all course exercise materials, including books on doing network research and ERGM.
Lunch and afternoon tea is provided.
Download the SNA Flyer 2018.
For any enquiries, please email Dr Peng Wang, Centre for Transformative Innovation.
Day 1: 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
- Group allocation and briefing
Day 2: Key Concepts & Descriptive SNA
Key Concepts & Descriptive SNA
- Social Selection vs Social Influence
- The building blocks of networks: density; reciprocity; degree; connectivity; centrality; clustering; and preferential attachment (popularity)
- Multiplex and bipartite networks
- Introductory approaches to statistical inference
Day 3: Introduction to ERGMs
Introduction to ERGMs
- What are exponential random graph models (ERGMs)?
- Formation of network structure
- MPNet software for network models
- Working with graph distributions
- Network dependence & emergence
- Estimating ERGMs (modelling network data)
Day 4: ERGM extensions
- Simulation and Goodness of Fit with ERGM
- Estimating directed ERGMs
- Estimating ERGMs with actor attributes
- ALAAMs – social influence models
- Problem solving for model fit
Day 5: Network Evaluation & Presentations
Network Evaluation & Presentations
- Network evaluation
- Network problem solving
- Group presentations