Events

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
Standard: $ 3,000.00
Full-time PhD students: $ 1,500.00
Swinburne staff: $ 1,500.00
Swinburne PhDs: $ 900.00

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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.

Contact Information: Dr Peng Wang, Centre for Transformative Innovation
Email: pengwang@swin.edu.au Tel: 03 9214 8230

Venue Location:

Day 1: Network Fundamentals

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

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