Big Data in Social Sciences

The experiment: SensibleDTU—What does a social network look in real time?

‘Social Fabric’ is the name of an interdisciplinary research project intended to answer a range of questions about the importance of social networks. A major part of the project is the SensibleDTU experiment, whereby 1,000 new students at the Technical University of Denmark (DTU) are issued a smartphone that logs all their social interactions, thus supplying the project with a series of empirical datasets that form the basis of the survey itself. In addition, the experiment is a research object in and of itself, given that a part of the objective is to establish survey perspectives in the context of what is known as ‘Big Data research’—with emphasis on the inherent ethical and methodological issues.

New digital technologies employed

Smartphones were used as measuring instruments—known as ‘sociometers’—with a view to mapping social networks across different types of communication. Each smartphone is fitted with a special app that logs all social activities:

  • Email
  • Telephony
  • Texting
  • Online social activity
  • Captures their behaviour

Each smartphone collects between 50 and 100 MB of data per day; with 1,000 smartphones in use, this translates into 50–100 GB per day. It is only possible to analyse these constantly increasing volumes of data with the assistance of supercomputing.

The data collected—the social fabric—will surely generate new perspectives on social networks as they develop in real time. The project is intended to develop new tools for distinguishing social networks, and to analyse—both quantitatively and qualitatively—whether and how behaviour and information are transmitted within networks.

The project started out investigating social networks, but the data collected have also provided insight into health, the spread of illness, sleep patterns and more besides. The data have thus also become interesting to a broader academic circle as the empirical substantiation of a range of assumptions.

Future challenges

  • The project may contribute to analysing how considerations for ethics and the sanctity of private life are dealt with in research based on sensitive data.
  • The project seeks to promote the emerging field of computational social science

The film features

  • Professor David Dreyer Lassen, Department of Economics, University of Copenhagen
  • Associate Professor Sune Lehmann Jørgensen, DTU COMPUTE—Department of Applied Mathematics and Computer Science, Technical University of Denmark

The film includes graphics and visualizations prepared by

  • Carl Emil Carlsen, sixth sensor (introductory visualization with music)
  • Enys Mones, Postdoc at DTU Compute
  • Andrea Cuttone, PhD at DTU Compute.

The film is the work of Iben Julie Schmidt from Scientifica film.

 
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