Online Seminar Talk
New Opportunities to Enhance or Replace Conventional Web Survey Data
Melanie Revilla
Laboratory of Digital and Computational Demography, November 30, 2022
Melanie Revilla from the Institut Barcelona d'Estudis Internacionals explained the potential advantages of new measurement opportunities, but also the challenges that researchers are facing.
Abstract
The expansion of the Internet and the development of a range of new active and passive measurement tools, particularly on mobile devices, present exciting opportunities for researchers. Compared to conventional surveys, using these new measurement opportunities (e.g., visual data or metered data) could reduce respondent burden, improve data quality, and extend measurement into new domains, allowing to answer questions that could not be answered so far and to improve the decisions of key actors (e.g. government).
However, while many people speak about these ideas, very little research has implemented such possibilities, and even less has assessed the data quality associated with such approaches. Thus, there is a huge need for further research in this area.
In this presentation, Melanie Revilla will explain the potential advantages of these data, but also the challenges/risks that researchers are facing to use such data. Moreover, she will present some examples of the research that they are doing to learn more about these new data types, to help researchers using them in the best way possible.
About
Melanie Revilla is a survey methodologist researcher at IBEI (Institut Barcelona d'Estudis Internacionals). Since 2020, she is the Principal Investigator of the WEB DATA OPP project, funded by an ERC starting grant. This project investigates new measurement opportunities to complement or replace conventional survey data in order to get better or new insights. Before moving to IBEI, she was Deputy Director of the Research and Expertise Centre for Survey Methodology (RECSM) and adjunct professor at Universitat Pompeu Fabra (Spain). Her main areas of research include survey measurement errors, data quality, mode of data collection, web surveys, mobile participation, and metered data.