Academic Profile

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Oriol J. Bosch

Non-Stipendiary Research Fellow
Postdoctoral Researcher in Data Donation and Computational Methods at the Leverhulme Centre for Demographic Science

Oriol is a Postdoctoral Researcher in Data Donation and Computational Methods, working within Professor Melinda Mill’s ERC advanced grant CHRONO, and the Data4Science project. He is also a Research Fellow at the Research and Expertise Centre for Survey Methodology (Universitat Pompeu Fabra), where he collaborates in the ERC starting grant WEB DATA OPP.

As a computational methodologist, Oriol specialises in the use of survey and computational methods to understand how scientists can best collect and analyse new sources of data, such as digital trace data. Currently, he is mainly interested in developing new methodologies to improve the collection of digital data through web trackers and data donations, while quantifying and minimising their errors and biases.

Before joining Oxford, Oriol completed his PhD in Social Research Methods at The London School of Economics, an MSc in Survey Methods for Social Research from the University of Essex, and a BSc in Political Science from Pompeu Fabra University. Additionally, Oriol has extensive research experience, having worked as a researcher or consultant for The Alan Turing Institute, Wellcome Trust, University of Southampton, University of Mannheim, and the Institute for Social and Economic Research.

Oriol J. Bosch


  • Michaud, A., Bosch, O.J., and N. Sauger. (2023) “Can survey scales affect what people report as a fair income? Evidence from the cross-national probability-based online panel CRONOS.” Social Justice Research
  • Torcal, M., Carty, E., Comellas, J.M., Bosch, O.J., Thomson, Z., and D.Serani (2022). “The dynamics of political and affective polarisation: Datasets for Spain, Portugal, Italy, Argentina, and Chile (2019-2022).” Data in Brief 48, 1-16
  • Bosch, O.J., and M. Revilla (2022). “When survey science met web tracking: presenting an error framework for metered data.” Journal of the Royal Statistical Association: Series A, 1-29
  • Bosch, O.J., Revilla, M., Qureshi, D., and J.K. Hohne (2022). “A new experiment on the use of images to answer web survey questions.” Journal of the Royal Statistical Association: Series A, 1-26.
  • Bosch, O.J., and M. Revilla (2022). “The challenges of using digital trace data to measure online behaviors: lessons from a study combining surveys and
    metered data to investigate affective polarization” SAGE Research Methods Cases.
  • Bosch, O.J., and M. Revilla (2021). “The quality of survey questions in Spain: a cross-national comparison.” Revista Española de Investigaciones Sociológicas 175, 3-26.
  • Bosch, O.J., and M. Revilla (2020). “Using emojis in mobile web surveys for Millennials? A study in Spain and Mexico" Quality & Quantity.
  • Revilla, M., Couper, M.P., Bosch, O.J., and A. Asensio (2020). "Testing the use of voice input in a smartphone web survey.” Social Science Computer Review 38(2), 2017-224.
  • Bosch, O.J., Revilla, M. and E. Paura (2019). "Do Millennials differ in terms of survey participation?" International Journal of Market Research 61(4), 359- 365.
  • Revilla, M., Bosch, O.J., and W. Weber (2019). "Unbalanced 3-group Split- Ballot Multitrait-Multimethod design?" Structural Equation Modeling: A
    Multidisciplinary Journal 26(3), 437-447.
  • Bosch, O.J., Revilla, M. and E. Paura (2019). "Answering mobile surveys with images: an exploration using a computer vision API." Social Science Computer Review 37(5), 669-683.
  • Bosch, O.J., Revilla, M., DeCastellarnau, A. and W. Weber (2018). "Measurement reliability, validity and quality of slider versus radio button scales in an online probability-based panel in Norway." Social Science Computer Review 37(1), 119–132.