Grants

University of Pennsylvania

To develop new infrastructure for large-scale, generalizable virtual social science lab experiments

  • Amount $400,821
  • City Philadelphia, PA
  • Investigator Duncan Watts
  • Year 2020
  • Program Research
  • Sub-program Economics

Experiments conducted online, using subjects that participate via web interface instead of physically traveling to a lab, have significant advantages over their in-person counterparts. They are cheaper to field, for instance, and they can draw from a more diverse pool of potential test subjects, making inferences from their findings more robust. Setting up such virtual experiments, however, is not easy. Existing software support packages for online experiments have been developed as “end-to-end” platforms that are not very flexible, much less interoperable. Customizing this software to meet the eccentricities of any given experiment often requires special programming skill and patience. Funds from this grant support a project, led by Duncan Watts at the University of Pennsylvania and Abdullah Almaatouq at MIT, that seeks to make fielding online experiments easier for researchers of all kinds. Watts and Almaatouq aim to develop the first modular virtual experiment platform, one that subdivides an experimental design into independent, though interoperable, parts with standard interfaces. Friendly graphical controls will enable researchers and administrators to customize, reuse, and improve each module of an experiment without writing new code. One feature, for example, will be automatic recruiting tools that simplify the location and retention of participant panels that are large, diverse, and representative. Grant funds will allow Watts and Almaatouq to develop and launch an entire virtual environment that will facilitate running social science experiments that are faster, cheaper, more scalable, more complex, and more realistic than could take place in a physical laboratory. All code for this software environment, in addition to accompanying documentation, tutorials, and webinars, will be made freely available through a professional archive that makes it easy for experimenters to both preregister their experiments as well as to deposit their code, data, and documentation. Additional grant funds will support outreach and adoption activities designed to encourage use of the platform and to begin to build an open-source community of developers devoted to its maintenance and improvement.

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