Big Data Analysis for Social Scientists : Online - (3 Days)

This online course introduces you to the collection and analysis of socially-generated 'big data' using the R statistical software, with a focus on on network and text data collected from social media, (Twitter, YouTube and Reddit) and the WWW.



The course will be run over three days over the following schedule:


9.30am -11.00am: Instructional Zoom session (instructor provides demonstration and teaching)
11.00am-11.30am: Break
11.30am-1.00pm: Participants working on set exercises/activities (a Zoom session will allow the instructor to provide 1:1 assistance and also additional instruction to the group)
1.00pm-2.00pm: Lunch
2.00pm-3.30pm: Instructional Zoom session
3.30pm-4.00pm: Break
4.00pm-5.30pm:  Participants working on set exercises/activities



*Please note: Courses will run on Australian Eastern Daylight Time (GMT +11)

(ie Melbourne, Sydney, Canberra daylight savings time. There will be 5 different time zones to consider in Summer)



Level 3 - runs over 3 days

Prof. Robert Ackland is based in the School of Sociology at the Australian National University (ANU). He was awarded his PhD in economics from the ANU in 2001, and he has been researching online social and organisational networks since 2002. He leads the Virtual Observatory for the Study of Online Networks Lab ( which was established in 2005 and is advancing the social science of the Internet by conducting research, developing research tools, and providing research training. Robert has been teaching masters courses in online research methods and the social science of the internet since 2008 (undergraduate versions of the courses started in 2017) and in 2019 he began teaching a course on economic analysis of the digital economy. His book Web Social Science: Concepts, Data and Tools for Social Scientists in the Digital Age (SAGE) was published in July 2013. He created the VOSON software for hyperlink network construction and analysis, which has been publicly available since 2006 and has been used by around 3000 researchers worldwide, and he is a co-creator of the vosonSML and VOSONDash R packages for collecting and analysing social media network and text data.

Course dates: Monday 8 February 2021 - Wednesday 10 February 2021
Course status: Course completed (no new applicants)
Week 3
About this course: 

This master-class introduces participants to approaches for collecting and analysing network and text data from social media, (Twitter, YouTube and Reddit) and the WWW (hyperlink networks).


The main software used in the course is R, but we also introduce Gephi for advanced visualisation. Data collection is via the VOSON Dashboard and vosonSML R packages for collecting social media network and data. We also cover other important R packages for network and text analysis such as: igraph (network analysis and visualisation), quanteda (quantitative analysis of textual data), tidytext and tm (text mining), wordcloud (text word clouds).


The course will be particularly useful to academics and PhD students who want to become more computationally literate, and those from technical disciplines (e.g. computer science, engineering, information science) who want to become more familiar with social science approaches to big data research. The course will also be useful for people from industry and government whose work involves quantitative analysis of social media data, e.g. for marketing, social research, public relations, brand management, journalism, opinion analysis.

Course syllabus: 


Day 1

  • Introduction to vosonSML, VOSON Dashboard
  • RStudio and R refresher, including installing R packages
  • SNA using VOSON Dashboard & R/igraph – 1 (network plots, basic node-/network-level metrics)
  • Collecting Twitter data using VOSON Dashboard & vosonSML
  • Text analysis using VOSON Dashboard & R – 1 (text preparation, frequency counts & wordclouds)


Day 2

  • Collecting YouTube/Reddit data with VOSON Dashboard & vosonSML
  • SNA using VOSON Dashboard & R/igraph – 2 (clusters, creating subnetworks, coding node attributes - manually and via automated text analysis)
  • Text analysis in R – 2 (sentiment analysis, semantic networks)
  • Collecting WWW hyperlink networks with VOSON Dashboard and vosonSML


Day 3

  • SNA in R - 3 (Introduction to dynamic network analysis)
  • Text analysis in R - 3 (topic models, introduction to machine learning using text)
  • Introduction to Gephi
  • Introduction to creating reproductible reports in R using knitr and rmarkdown
  • Advanced topics (based on participant interest)



Course format: 

This masterclass will be run online, via Zoom.


To ensure that participants are well prepared for the masterclass, there will be detailed instructions to ensure that they have the required R, RStudio and other R packages pre-installed before the masterclass. There will also be preliminary exercises (introduction to R and RStudio) that the participants will be expected to complete before the masterclass. The instructor will be available for consultation (via email or Zoom) prior to the masterclass, to provide assistance with installation of software and the preliminary exercises.


The format of the masterclass (ball three days) will be:

9.00am -10.30am: Instructional Zoom session (instructor provides demonstration and teaching)
10.30am-11.00am: Break
11.00am-12.30pm: Participants working on set exercises/activities (a Zoom session will allow the instructor to provide 1:1 assistance and also additional instruction to the group)
12.30pm-1.30pm: Lunch
1.30pm-3.00pm: Instructional Zoom session
3.00pm-3.30pm: Break
3.30pm-5.00pm:  Participants working on set exercises/activities


Recommended Background: 

It is advisable that you have taken at least one of the following ACSPRI courses, or have had some equivalent exposure to social network analysis:


It is also advisable that you have some experience with the R programming language (or similar languages) for example, via the following ACSPRI courses:

Recommended Texts: 

There are no recommended texts, but you can find information on relevant software, (including how to download and install, and help information) here:



Course fees
Non Member: 
Full time student Member: 

Q: Should I have taken an ACSPRI R Course before attempting this course?

A: Not necessarily. However it is advisable that you either have some experience with social network analysis or experience with R (or a similar programming language).


Q: Do I need to have the VOSON Dashboard and vosonSML R packages already installed on my computer?

A: Yes. Instructions and assistance will be provided prior to the commencement of the course, to ensure that these packages (and R, Rstudio) are successfully installed.


Participant feedback: