This course will provide students with an introduction to social media analysis in the context of social research.
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 (http://vosonlab.net) 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). 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 was publicly released in 2006. The VOSON R packages for collecting and analysing social media network and text data were released in 2015 (Bryan Gertzel is the lead developer), and to date the packages have been downloaded over 80K times with current downloads of 1K per month.
This course is designed for social researchers interested in studying social media, and covers methods of accessing and analysing digital trace data (also known as “big data”) from websites, blogsites, Twitter and Facebook.
While there is emphasis on techniques from social network analysis (for analysing, for example, WWW hyperlink networks, follower networks in Twitter, friendship networks in Facebook), the course also covers analysis of text content. The course also provides practical training in three software tools that can be used for social research using digital trace data: VOSON (for hyperlink network construction and analysis), NodeXL (an Excel 2007/2010 template for collecting and analysing social media data) and Gephi (for network visualisation). The course also provides a broad overview of online research methods, including an introduction to using Virtual Worlds (e.g. Second Life and Massively Multiplayer Online Games) and online experiments for social research.
The following is an indicative list of topics covered during the course. Prior to the course running we will ascertain student interest in particular topics and focus the course accordingly.
Day 1
- Welcome and introduction to course
- Lecture: Social Media and Big Data
- Lecture: Introduction to Social Network Analysis
- Practical session: Getting started with NodeXL; Introduction to SNA in NodeXL
- Setting up VOSON accounts, installing additional NodeXL plugins, Class projects
Day 2
- Lecture: WWW hyperlink networks
- Practical session: Using VOSON to collect WWW hyperlink and website content data
- Lecture: Social Network Sites (e.g. Facebook)
- Practical session: Using NodeXL to collect Facebook personal network data
Day 3
- Lecture: Microblogs (e.g. Twitter)
- Practical session: Using NodeXL to collect and analyse Twitter data
- Lecture: Threaded conversation networks
- Practical session: Using NodeXL to collect and analysis Facebook fan page data
Day 4
- Lecture: Quantitative text analysis
- Practical session: Using NodeXL for quantitative text analysis
- Practical session: Advanced VOSON
- Practical session: Introduction to Gephi
Day 5
- Lecture: Other online research methods (e.g. virtual worlds, online experiments)
- Practical session: Advanced Gephi
- Project presentations
You will be advised in advance whether this course will be run in a computer lab or whether you will have to bring your own laptop.
If the course is run with participants using their own laptops, you will need to have installed:
- Firefox/Chrome/Safari web browser and a VOSON user account (free for course participants);
- NodeXL (this is a template for Excel 2007/2010/2013 and only runs on Windows);
- Gephi (this runs with Mac/Windows/Linux).
The course assumes participants have good familiarity with using computers, in particular web applications.
Participants are advised to have taken the ACSPRI course Introduction to Social Network Analysis for Social Researchers or had some equivalent exposure to social network analysis or quantitative text analysis.
- Ackland, R. (2013), Web Social Science: Concepts, Data and Tools for Social Scientists in the Digital Age, SAGE Publications.
- D. Hansen, B. Shneiderman and M. Smith (2010), Analyzing Social Media Networks with NodeXL: Insights from a connected world. Morgan-Kaufmann.
Q: Do I need any prior knowledge before taking this course?
A: You are advised to have taken the ACSPRI course Introduction to Social Network Research Analysis for Social Researchers or have the equivalent experience.
Q: Does this course involve programming or coding?
A: No, this course is conducted entirely with software with graphical user interfaces (GUIs) – there is no programming involved (other than some advanced Excel commands). If you want to do a programming course on social media analysis, the Big Data Analysis for Social Scientists course may be what you are looking for.
Q: Will I need to bring any any software to this course?
A: Yes, see the course format section for details.
A new technique to apply to research projects. (Winter 2014)
It has provided info on the main tools available as well as further resources. (Winter 2014)
The instructor's bound, book length course notes will serve as the course texts.