The UK Data Service is pleased to release open learning materials from its training series: Computational Social Science (previously known as New Forms of Data for Social Science Research). Vast swathes of our social interactions and personal behaviours are conducted online and/or captured digitally. Our use of social media platforms such as Facebook, Twitter and Instagram generates astounding amounts of data, much of which is available from these platforms if you have the right programming skills. Snapshots of our daily lives are routinely captured and aggreagted into large, rich administrative datasets. Websites can be scraped and marshalled into statistically-usable datasets, and documents aggregated into large corpora of text information that can be mined for interesting patterns (e.g., through sentiment analysis). Thus, computational methods for collecting, processing and analysing new forms of data are an increasingly important component of a social scientist’s toolkit.
We have provided sample code, webinar recordings and slides, reading lists, FAQs and more for each of the topics covered under the Computational Social Science training series:
- Agent-based Modelling
- Web-scraping for Social Science Research
- Programming for Social Science Research
- Being a Computational Social Scientist
- Text Mining
- Social media/network Data
We have also written guidance for installing Python and other packages on your machine: [Instructions]
We are grateful to UKRI through the Economic and Social Research Council for their generous funding of this training series.
- To keep up to date with upcoming and past training events: [Events]
- To get in contact with feedback, ideas or to seek assistance: [Help]
Thank you and good luck on your computational social science journey!
Dr Julia Kasmire
UK Data Service
University of Manchester