The utility of digital trace data to understand how people search for jobs online

Abstract

Abstract

This study explores the utility of metered data, a specific form of digital trace data, for analyzing online job-seeking behaviors in Spain. Using nine months of data from 600 participants, it evaluates which job search-related concepts can be measured and the impact of two factors on the resulting indicators: the devices used to gather the data and the data collection period. Findings reveal that metered data can effectively operationalize concepts like job search effort and platform use, avoiding recall biases inherent in surveys. However, offline-dependent concepts like reemployment efficacy and subjective concepts like job-search anxiety remain unsuitable for metered data. Additionally, metered data collected from online panels allow comparisons of indicators among groups defined by profiling information and online behaviors. Results are sensitive to researchers’ decisions regarding the type of devices tracked (PC vs. mobile) and the extent of the data collection period. Researchers should try to gather data from both types of devices and ensure the data collection period is long enough to allow robust estimations of the concepts of interest. By exploring online job searches, this research shows metered data's potential to enhance the understanding of online activities, offering precise and granular insights that can complement or replace conventional survey methods. Understanding online behavior is increasingly critical as many daily activities, such as job searches, which have significant societal and individual impacts, transition to digital platforms.