IEEE Access (Jan 2019)

Latent: A Flexible Data Collection Tool to Research Human Behavior in the Context of Web Navigation

  • Catia Cepeda,
  • Ricardo Tonet,
  • Daniel Noronha Osorio,
  • Hugo P. Silva,
  • Edouard Battegay,
  • Marcus Cheetham,
  • Hugo Gamboa

DOI
https://doi.org/10.1109/ACCESS.2019.2916996
Journal volume & issue
Vol. 7
pp. 77659 – 77673

Abstract

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Internet usage has grown dramatically since the early years of its inception. The rich field of data provided by internet users in interaction with digital media content can provide insight into web-based navigation behavior and underlying psychological dimensions. Human-computer interaction in the web is an underutilized source of data for understanding human online behavior. While researchers and usability testing services do use these sources to analyze human behavior and user experience, access to the diverse range of other potentially useful data available during web-based interaction for research is limited. In this paper, we propose a novel tool in the form of a web browser extension, referred to as Latent, which can be used to simultaneously capture information from different sources while users interact with digital content. The data acquisition capabilities of Latent makes it suitable for various research purposes, ranging from studies of usability to decision-making and personality. A particular advantage of Latent is that the method and control of data acquisition is completely transparent to the user. We present the architecture of the web browser extension, describe the data that can be acquired, and report on the residual impact of the tool on the user's computer processing resources.

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