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As digital technologies, the internet and social media become increasingly integrated into society, our daily lives generate unprecedented quantities of digital data. These data provide opportunities to study complex social systems in frameworks similar to those of the natural sciences with emphasis on empirical observation of patterns in large-scale data, quantitative modelling and experiments. This ‘social data science’ can generate theory-informed predictive models and underpin the way we understand and solve social problems.




The Internet presents huge opportunities for accessing and analysing data around a whole range of human activities: and getting their hands dirty with “real” data is something our Masters students are encouraged to do. Our MSc methods course options cover a whole arc from accessing research data from the social web, to wrangling data, and finally information visualisation and big data analytics.

Students taking these courses have looked at the diffusion of hashtags on Instagram, the use of Twitter for prediction, spread of discourses on social media, the language behind political satire, have analysed the distribution of Wikipedia article length to establish a better measure of language edition size to better understand growth and sustainability of the project, and have investigated popularity patterns of posts on Instagram to model meme virality.