This course introduces students to the collection and analysis of socially-generated 'big data' using the R statistical software and Gephi network visualisation software.
Big data involves data on: (1) people (social web) e.g. online social networks (e.g. Facebook), microblogs (e.g. Twitter); (2) information (WWW) e.g. web pages, clickstreams; (3) things (sensor web) e.g. phones, temperature sensors, and (4) places (geospatial web) e.g. geology, land use maps.
The focus of this course is on data from the social web and the WWW. Students will learn how to: (1) collect data from web pages, Twitter and Facebook; (2) construct, analyse and visualise networks of people and organisations (social networks) and terms (semantic networks); (3) extract and analyse text data; (4) conduct temporal analysis, (5) filter and sample from large datasets; (6) identify and engage with advanced techniques for dealing with very large datasets.
We will focus on three sources of network and text data: Twitter, Facebook and the WWW. We will look at:
The course will also provide an opportunity for students to learn about examples of 'best practice' social science big data research, and thus see how these data and techniques are already being used in social science.More information: https://www.acspri.org.au/winterprogram2015/big-data-analysis-social-scientists
Associate Professor and Deputy Director (Education), Australian Demographic and Social Research Institute
Leader, Virtual Observatory for the Study of Online Networks (VOSON) Lab
Australian National University
Web Social Science: Concepts, Data and Tools for Social Scientists in the Digital Age (SAGE Publications)
about the Master of Social Research (Social Science of
the Internet specialisation):