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.