Willingness to participate in in-the-moment surveys triggered by online behaviors

When survey science met web tracking: Presenting an error framework for metered data

Metered data, also called web-tracking data, are generally collected from a sample of participants who willingly install or configure, onto their devices, technologies that track digital traces left when people go online (e.g., URLs visited). Since metered data allow for the observation of online behaviours unobtrusively, it has been proposed as a useful tool to understand what people do online and what impacts this might have on online and offline phenomena. It is crucial, nevertheless, to understand its limitations. Although some research have explored the potential errors of metered data, a systematic categorisation and conceptualisation of these errors are missing. Inspired by the Total Survey Error, we present a Total Error framework for digital traces collected with Meters (TEM). The TEM framework (1) describes the data generation and the analysis process for metered data and (2) documents the sources of bias and variance that may arise in each step of this process. Using a case study we also show how the TEM can be applied in real life to identify, quantify and reduce metered data errors. Results suggest that metered data might indeed be affected by the error sources identified in our framework and, to some extent, biased. This framework can help improve the quality of both stand-alone metered data research projects, as well as foster the understanding of how and when survey and metered data can be combined.

Willingness to participate in geolocation-based research

Among the new research possibilities offered by smartphones, collecting geolocation data (e.g., GPS coordinates) holds a prominent position, allowing the investigation of individuals' mobility with greater precision and less effort than conventional data collection methods. However, geolocation data are still affected by errors (e.g., inaccurate recorded locations) and limitations (e.g., inability to record the purpose of a trip). Sending a survey right in the moment an event of interest is detected using geolocation data can add the missing information, while reducing memory errors that typically affect conventional surveys (sent some days/weeks after). However, the possibilities offered by both geolocation data and in-the-moment surveys triggered by geolocation data are limited by individuals' willingness to participate. This paper assesses such willingness using a conjoint experiment carried out on a sample of 1,016 members of an opt-in online panel in Spain. The effects on such willingness to accept the conditions offered to participants and their personal characteristics are also studied. The results show that asking panelists to participate in in-the-moment surveys does not negatively affect willingness compared to only sharing geolocation data. However, the conditions offered to panelists for their participation (mainly project duration and incentives) have a strong influence on their willingness. Furthermore, panelists less concerned with privacy and safety, and more experienced in sharing social media content, installing apps and using Google Maps, are more willing to participate. Finally, answers to open questions reveal that the main reason for participating is getting the incentive, while not participating is primarily related to privacy issues.