webgazeR

An R package for reading, preprocessing, and analyzing webcam-based eye-tracking data. A companion to gazeR, webgazeR provides a complete pipeline from raw files to analysis-ready data for experiments run on Gorilla, jsPsych, PsychoPy, or Labvanced.

Installation

# From R-Universe (recommended)
install.packages("webgazeR",
  repos = c("https://jgeller112.r-universe.dev", "https://cloud.r-project.org"))

# From GitHub
# install.packages("remotes")
remotes::install_github("jgeller112/webgazeR")

Supported Platforms

Platform	Input format	Notes
Gorilla	.xlsx / .csv	Filters type == "prediction" rows; supports screen index selection
jsPsych	.json / .csv / .tsv	Handles JSON trials exports and tabular formats with nested gaze arrays; flattens webgazer_targets into columns regardless of shape
PsychoPy	.csv / .tsv	Tabular trial-level data with nested eye sample arrays; converts time from seconds to milliseconds
Labvanced	.csv	Combines a timeseries export with its optional trials/sessions exports; supports multi-participant folders

Documentation

• Package website
• Introduction vignette -- Full walkthrough with interactive code
• ISC guide -- Intersubject correlation methods
• Using webgazeR with Labvanced
• Using webgazeR with jsPsych
• Using webgazeR with PsychoPy

Citation

If you use webgazeR in your research, please cite:

Geller, J., Prystauka, Y., Colby, S. E., & Drouin, J. R. (2025). Language without borders: A step-by-step guide to analyzing webcam eye-tracking data for L2 research. Research Methods in Applied Linguistics. https://doi.org/10.1016/j.rmal.2025.100

License

GPL-3