Exploring the potential of big data for Eurofound research
Surveys have never been the only source of large-scale, quantitative data, and discussions about better integrating data from other sources in social research have been ongoing for quite some time. However, in recent decades, with the increasing connectedness of individuals and organisations to the internet, the amount of data available from sources such as web applications, mobile devices, sensors, video streams and social media has exploded.
In this context, Eurofound is exploring the potential use of big data to complement and contextualise the data from its existing research efforts, its surveys in particular. The project currently focuses on three strands, and this work is discussed in three working papers.
- Working paper: Using big data to improve survey sampling
Reflects on the current and possible future opportunities for using big data to enhance sampling frames or even to generate sampling frames for online surveys, and examines the extent to which a full probability approach is achievable or can at least be approximated. Also discusses the possible gains in efficiency.
- Forthcoming: Collecting and analysing big quantitative data: Statistical analysis and machine learning
Offers insight into the most appropriate analytical techniques for collecting and analysing ‘true’ big data (such as the number of people visiting a place or doing an action online, movements of people based on mobile data, and geolocation). Indicates where approaches differ from ‘regular’ statistical analysis, highlights techniques that Eurofound would need to familiarise itself with, and describes the software and hardware requirements.
- Forthcoming: Using text analysis of social media content to investigate marginal phenomena
Explores the potential and limitations of using social media content as a data source and of the various social media platforms to which this approach could be applied (for example, Facebook, LinkedIn and Twitter), using one or more practical examples.