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
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
