ASNAC 2020 Workshop schedule: Wed 25 November 2020

Location: All workshops will be delivered on-line. Times are Australian Western Standard Time (Perth GMT +8).

Cost per workshop: $50 (+GST of $5)

Workshops will be capped at 30 participants.

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Workshop 1: 11:30pm-1pm AWST (2:30pm-4:00pm AEST)

Introduction to Social Network Research

Instructors: Malcolm Alexander (Griffith University), Petr Matous (University of Sydney), Daniel Chamberlain (La Trobe University)

This workshop surveys the range of research approaches coming from long-standing social science work on Social Network Analysis (SNA). It provides guidance for social researchers interested in the substantive questions around social networks by looking at the type of findings produced by SNA research built on survey and (ego-centric) egonet methods, (socio-centric) whole network analysis, and affiliation (2-mode) data. We briefly review the modelling and simulation of ‘complex networks’ and probabilistic network models such as exponential random graph modelling or stochastic actor-oriented modelling.

This workshop will cover the fundamental concepts of the three social network research streams and help you choose the strategy of network research best suited to your goals and data availability. We will also outline the variety of software available for handling network data, visualising networks, SNA analytics and network modelling.

1: Introduction and stocktake of participants’ research needs.

2: Survey research and ego-centric (egonet) studies: Their contribution to network thinking.

3: SNA’s socio-centric ‘whole network’ approaches: Examples.

4: The road toward statistical and ‘complex’ network modelling.

5: Where do I start? Data collection and management, Software packages.

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Workshop 2: 11:30pm-1pm AWST (2:30pm-4:00pm AEST)

Hands-on introduction to SAOMs for newbies

Instructor: Johan Koskinen (University of Melbourne, Social Networks Laboratory)

This is a 90 minute workshop that will give you hands-on experience in fitting a stochastic actor-oriented model to longitudinal networks using RSiena in R. The workshop is based around simple example of longitudinal network and aims to illustrate how to calibrate (estimate) the SAOM so that the simulation model reproduces the second network starting in the first. No prior experience of R is required and the workshop will walk you through pre-prepared code that will be provided. Basic knowledge about SNA and a laptop with R and the packages RSiena, sna, and network (instructions for installation are provided here http://www.stats.ox.ac.uk/~snijders/siena/siena_r.htm). More background material will be provided on the website.

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Workshop 3: 11:30pm-1pm AWST (2:30pm-4:00pm AEST)

Introduction to ERGMs for beginners

Instructors: Peng Wang, Colin Gallagher, James Coutinho, Maedeh Aboutalebi Karkavandi, Dean Lusher (Swinburne University, MelNet Social Network Research Group)

This 90 minute workshop will provide you with practical experience in fitting an exponential random graph model (ERGM) to cross-sectional network data using MPNet. The workshop is based around simple example of an undirected network. It aims to demonstrate how to calibrate (estimate) the ERGM so that the simulation model reproduces the observed network data based on the set of actors (nodes) and their individual attributes (characteristics). The workshop will walk you through the basic rationale behind ERGM framework, formatting data, and using the MPNet program. No programming knowledge is required. Basic knowledge about SNA and a Windows laptop are needed. More background material will be provided on the website.

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Workshop 4: 1pm-2:30pm AWST (4:00pm-5.30pm AEST)

VOSON Lab Tools for Collecting and Analysing Online Networks

Instructor: A/Prof Robert Ackland (Virtual Observatory for the Study of Online Networks (VOSON - http://vosonlab.net ) Lab & School of Sociology, Australian National University)

This workshop will introduce participants to two open source R packages for online network collection and analysis:

vosonSML (https://github.com/vosonlab/vosonSML ) - an R package providing a suite of tools for collecting and constructing networks from social media data. It provides easy-to-use functions for collecting data across popular platforms (Twitter, Reddit and YouTube) and generating different types of networks for analysis.
VOSON Dashboard (https://github.com/vosonlab/VOSONDash ) - an R/Shiny application providing a graphical user interface for collecting and analysing online networks and associated text data. It builds on a number of R packages, in particular igraph (for network analysis) and vosonSML.

Participants will be shown how to install vosonSML and VOSON Dashboard, and the basic operation of these tools. Workshop materials will include notes on analysis of online networks, and examples of research.

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Workshop 5: 1pm-2:30pm AWST (4:00pm-5.30pm AEST)

A review of advanced use of SAOM

Instructor: Johan Koskinen (University of Melbourne, Social Networks Laboratory)

This is a 90 minute workshop with brief examples of extensions to stochastic actor-oriented model to longitudinal networks. It is assumed that you have some basic experience of using the standard selection and influence models, including running standard diagnostics. We will cover some recent extensions, such as analysis of multiplex ties, the joint evolution of one-mode and two-mode networks, influence models for continuous outcomes, and multilevel analysis using multigroup and sienaBayes. A focus will be put on data formats and some key interpretative issues in working with the output. Example code will be provided and a laptop with R and the packages RSiena, sna, and network is required for following the workshop.

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Workshop 6: 1pm-2:30pm AWST (4:00pm-5.30pm AEST)

An overview of advanced uses of ERGMs

Instructors: Peng Wang, Colin Gallagher, James Coutinho, Maedeh Aboutalebi Karkavandi, Dean Lusher (Swinburne University, MelNet Social Network Research Group)

This is a 90 minute workshop with brief examples of extensions to exponential random graph models. The focus of this course will be on more advanced forms of cross-sectional network data, including directed, bipartite, and multilevel network data. It is assumed that you have some basic experience of using the standard selection models (e.g., ERGMS). Example datasets will be provided. A focus will be put on data formats, common trouble shooting, and some key interpretative issues. A Windows laptop is required for following the workshop.