Publications
You can also find my articles on my Google Scholar profile
Peer-reviewed publications
Published in Journal of the Royal Statistical Society: Series A, 2022
In this paper we present a Total Error Framework for Digital Trace Data / Web Tracking data. We show how to use web tracking to measure what people do online, the errors to expect when doing so, and best practices informed by a real case study Read more
Recommended citation: 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: https://doi.org/10.1111/rssa.12956 https://doi.org/10.1111/rssa.12956
Published in Journal of the Royal Statistical Society: Series A, 2022
In this experiment we explore the impact on several data quality indicators of asking participants to answer open-ended questions with images, instead than with text Read more
Recommended citation: Bosch, O.J., Revilla, M., Qureshi, D.D. & Höhne, 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. Available from: https://doi.org/10.1111/rssa.12856 https://doi.org/10.1111/rssa.12856
Published in SAGE Research Methods Cases, 2022
This case study describes the data collection strategy of the TRI-POL project, which represents the first attempt to collect both longitudinal survey and digital trace data, from the same individuals, to understand whether and how the Internet and social media are related to affective polarization across Southern European and Latin American countries Read more
Recommended citation: Bosch, O. J., & 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.In SAGE Research Methods Cases. https://dx.doi.org/10.4135/9781529603644 https://methods.sagepub.com/case/digital-trace-data-measure-online-behaviors-surveys-metered-data
Published in Spanish Journal of Sociological Research, 2021
Using a Split-Ballot Multitrait-Multimethod experiment conducted in the European Social Survey round 8, we compare the quality of questions in Spain with their quality in other participating countries, as well as the consequences of not accounting for measurement errors when conducting cross-national research Read more
Recommended citation: Bosch, O. J., & Revilla, M. The quality of survey questions in Spain: a cross-national comparison. Revista Española de Investigaciones Sociológicas, 175: 3-26. http://www.reis.cis.es/REIS/PDF/REIS_175_01_ENG1623064444202.pdf
Published in Quality and Quantity: International Journal of Methodology, 2020
In this article we determine how emojis can be used in mobile web surveys, in particular in open-ended questions, and how their use can affect data quality, completion time, and survey evaluation Read more
Recommended citation: Bosch, O. J., & Revilla, M. Using emojis in mobile web surveys for Millennials? A study in Spain and Mexico. Quality & Quantity: International Journal of Methodology, 1-23. https://link.springer.com/article/10.1007/s11135-020-00994-8
Published in Social Science Computer Review, 2020
We implemented an experiment within a smartphone web survey to explore the feasibility of using voice input (VI) options to answer open-ended questions. Read more
Recommended citation: Revilla, M., Couper, M. P., Bosch, O. J., & Asensio, M. (2020). Testing the use of voice input in a smartphone web survey. Social Science Computer Review, 38(2), 207-224. https://journals.sagepub.com/doi/abs/10.1177/0894439318810715
Published in International Journal of Market Research, 2019
Using a dataset of 1,570,301 panelists of an opt-in online panel in eight countries from Europe, Latin America, and North America, we show that Millennials differ from older cohorts in terms of survey participation Read more
Recommended citation: Bosch, O. J., Revilla, M., & Paura, E. (2019). Do Millennials differ in terms of survey participation?. International Journal of Market Research, 61(4), 359-365. https://journals.sagepub.com/doi/abs/10.1177/1470785318815567
Published in Structural Equation Modeling: A Multidisciplinary Journal, 2019
In this article we investigate if groups of unequeal sample sizes can be used in 3-group split-ballot multitrait-multimethod (SB-MTMM) experiments Read more
Recommended citation: Revilla, M., Bosch, O. J., & Weber, W. (2019). Unbalanced 3-Group Split-Ballot Multitrait–Multimethod Design?. Structural Equation Modeling: A Multidisciplinary Journal, 26(3), 437-447. https://www.tandfonline.com/doi/abs/10.1080/10705511.2018.1536860
Published in Social Science Computer Review, 2019
In this article we investigate the viability of asking respondents of an online opt-in panel to upload during a mobile web survey: First, a photo taken in the moment, and second, an image already saved on their smartphone. In addition, we test to what extent the Google Vision application programming interface (API) produces similar tags than a human coder. Read more
Recommended citation: Bosch, O. J., Revilla, M., & Paura, E. (2019). Answering mobile surveys with images: an exploration using a computer vision API. Social Science Computer Review, 37(5), 669-683. https://journals.sagepub.com/doi/abs/10.1177/0894439318791515
Published in Social Science Computer Review, 2019
We estimate the measurement quality of sliders compared to radio button scales controlling for the device respondents used. To do so conducted two multitrait–multimethod (MTMM) experiments in the Norwegian Citizen Panel (NCP), a probability-based online panel. Read more
Recommended citation: Bosch, O. J., Revilla, M., DeCastellarnau, A., & Weber, W. (2019). 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. https://journals.sagepub.com/doi/abs/10.1177/0894439317750089
Reports and Non Peer-reviewed publications
MoneyHelper, ISER Working Paper Series, 2021
This reports evaluates and analyses a pilot longitudinal survey of people in debt in the UK (2,025 participants). We report methodological lessons learned, aimed at identifying the best procedures to use on the new survey, and provide estimates of the sample size that would be needed. Read more
Recommended citation: Bosch, Oriol & Lynn, Peter, 2021. "Methodological lessons from the pilot longitudinal survey on debt advice," ISER Working Paper Series 2021-03, Institute for Social and Economic Research. https://finchley.essex.ac.uk/research/publications/working-papers/iser/2021-03.pdf
RECSM Working Papers Series, 62, 2021
In this paper we present a framework of all errors that can occur when using metered data. To do so, we adapt the Total Survey Error framework to accommodate it to the specific error generating processes and error causes of metered data Read more
Recommended citation: Bosch, O.J., and M. Revilla (2021) When survey science met online tracking : presenting an error framework for metered data. http://hdl.handle.net/10230/46482 https://www.upf.edu/documents/3966940/6839730/WP62.pdf/16aaf443-c545-2f5a-faac-a2bb55dec4d6
ESS ERIC, Workpackage 5, 2018
In this reports we analyze the measurement quality of several survey questions included in Round 8 of the European Social Survey Read more
CRONOS, Work Package 7: A survey future online, 2018
In this reports we establish the impact of motivational messages in web surveys on data quality, using an experiment conducted in waves 2, 4 and 6 of the CROss-National Online Survey (CRONOS) panel Read more
Recommended citation: Bosch, O.J., Weber, W., and M. Revilla (2018) Improving web panel respondent behaviour: The effect of encouragement messages throughout the course of the survey. Deliverable 7.12of the SERISS project funded under the European Union’s Horizon 2020 research and innovation programme GA No: 654221. Available at: https://seriss.eu/wp-content/uploads/2018/10/SERISS-Deliverable-7.12-Strategies-to-improve-panelist-responding-behaviour.pdf