The deputy director of the UPF Research and Expertise Centre for Survey Methodology, which in 2019 received a grant from the European Research Council to study the subject, gave one of the keynote speeches at the 2021 conference of the European Survey Research Association (ESRA).
Melanie Revilla presented the state of research regarding the use of new types of data that may replace or complement survey data, their potential benefits and associated challenges
In her speech entitled " How to Enhance web survey data and get better insights ", Melanie Revilla presented new methods in the field of survey methodology, the result of the cutting-edge research she is conducting. She was one of the two keynote speakers, invited by the conference organizers, in recognition of her experience and expertise in a particular area. This ESRA 2021 conference , which takes place biennially, is being held through a series of online sessions during the month of July.
Melanie Revilla presented the state of research regarding the use of new types of data that may replace or complement survey data, their potential benefits and associated challenges. It is linked to her research project WEB DATA OPP ("New opportunities to enhance or extend (mobile) web survey data and get better insights") for which she received an ERC Starting Grant from the European Research Council in its 2019 announcement. In her project, which will run until the 2024, she will take advantage of the growing number of mobile devices and ubiquitous connectivity to obtain a more accurate and complete view of the reality and the potential of " (mobile) web surveys ", and help key players make better decisions.
An emerging research area with great potentialIn her ESRA 2021 conference speech, Melanie Revilla reflected on the fact that the expansion of the Internet and the development of a range of new active and passive measurement tools, especially on mobile devices, offers exciting opportunities for researchers. However, she noted that to date there is very little research to have implemented these possibilities and have assessed the quality of the data associated with these approaches, which is a gap she is attempting to fill through her project.
"Compared to conventional surveys, the use of these new measuring opportunities could reduce the effort by respondents, improve data quality and extend measurement to new domains, which would enable responding to questions that have not been possible to answer so far and improve the decisions of the key stakeholders, such as governments", Melanie Revilla asserted.
Four types of data that can be provided by web surveysMelanie Revilla focused on four new data types. The first two are passive data: data collected by a tracker installed on the respondent’s smartphone or personal computer , which relate to the URLs of websites visited by participants on their devices, along with information about the time of each visit and use of the application; and geolocation data , which relate mainly to GPS coordinates: survey respondents need only accept to share these data and install a tracking application. Then, the data are received in real time by the fieldwork company, without any further requirement of the participants.
The other two types of data must be provided by the respondents actively and consist of visual data (screenshots, photos and videos obtained during the survey or already stored on their device) and voice data (voice recording captured during the survey). "These data may help to reduce several problems that affect the quality of survey data, such as those related to the limitation of the human memory or lack of effort on the part of the respondents", the researcher assures.
In her speech, Melanie Revilla outlined other potential advantages of such surveys (e.g., they enable disposing of large amounts of data), and also disadvantages, such as the difficulty of ensuring the informed consent of participants and that they are aware of all of the information they are sharing. She also identified several future lines of research to implement these new data types, including studying when and how they should be used or creating new guidelines or recommendations for use.