Oriol Bosch-Jover

Oriol Bosch-Jover

Research Student

Department of Methodology

Connect with me

Catalan, English, Spanish
Key Expertise
Survey Methodology, Data Quality, Political Behaviour, Fake News

About me

Oriol Bosch is a fourth-year PhD candidate in Social Research Methods supervised by Professor Patrick Sturgis and Professor Jouni Kuha. He is also a Research Assistant at The Alan Turing Institute and a Non-Resident Researcher at the Research and Expertise Centre for Survey Methodology (RECSM).

As a methodologist, Oriol focuses on understanding how to better collect and analyse attitudinal and behavioural data for the social sciences. He specializes in topics related to web and mobile surveys and the use of digital trace data and sensors to enhance or substitute surveys. His work, published in journals such as Social Science Computer Review or the Journal of the Royal Statistical Society, has explored the measurement quality of survey scales in online surveys using MTMM experiments; the generational divides between participants in terms of survey behaviour and data quality; and the impact on data quality of using novel data types to answer survey questions such as images, voice memos and emojis.

For his PhD, he is focusing on understanding how social scientists can best collect information about citizens’ online behaviours using web trackers, e.g., apps that can track the URLs and apps through that individuals visit. Through a combination of theory and traditional survey and computational methods, his research explores how to quantify and minimize metered data errors, while comparing them with the ones of surveys

Oriol is also involved or has been involved in several international research projects, such as the ERC’S WEB DATA OPP project, TRI-POL, GenPopWeb2 network, Netquest Research Lab and the CROss-National Online Survey (CRONOS). Apart from his academic background, he frequently works as a consultant for for non-profit organisations and public bodies. So far he has collaborated with the Wellcome Trust, the Social Care Institute for Excellence and MoneyHelper, helping them better design and analyse socially relevant surveys.


Bosch, O.J., Revilla, M. (2022) "When survey science met web tracking: presenting an error framework for metered data". Journal of the Royal Statistical Society: Series A (Statistics in Society), 1-29: 

Bosch, O.J., Revilla, M., Qureshi, D.D., Hohne, J.K. (2022)."A new experiment on the use of images to answer web survey questions". Journal of the Royal Statistical Society: Series A (Statistics in Society). 1–26.

Bosch, O.J. and Revilla, M. (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 Revilla, M. (2021). “The Quality of Survey Questions in Spain: A CrossNational 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.