ArticleBehavior research methods2026
GazePlotter: An open-source solution for the automatic generation of scarf plots from eye-tracking data.
Article in Behavior research methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Advancing eye movement analysis through compositional modeling: A new perspective on Yarbus' classic study.Behavior research methods · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Eye-tracking is widely used to study perception, learning, and decision-making, yet visualising temporally structured gaze behaviour remains challenging. Scarf plots (also known as sequence charts) help illustrate when and where participants focus attention, but existing tools are often proprietary, static, or require programming expertise. GazePlotter is an open-source, browser-based application designed to lower these barriers. GazePlotter automatically processes raw exports from six eye-tracking software tools, including Tobii Pro Lab and GazePoint Analysis, and generates interactive, customisable scarf plots. It supports dynamic areas of interest (AOIs), multiple timeline modes (absolute, relative, ordinal), and enables side-by-side comparisons across participants, groups, or stimuli. Complementary visualisations-such as bar charts and transition matrices-can be combined within interactive dashboards. The application runs entirely in the browser (available at https://gazeplotter.com ), preserving data privacy and requiring no installation or registration. Its data pipeline-from import through parsing, AOI aggregation, and export-was validated against proprietary software outputs, with high agreement across key metrics. Parsing is memory-efficient and tested on multi-gigabyte datasets, with consistent functionality across Chrome, Firefox, Safari, and Edge. A task-based usability evaluation demonstrated successful task completion and positive perceived pragmatic and hedonic quality among participants with prior experience in eye-tracking methodology. By enabling non-programmers to create exploratory visualisations directly from raw exports, GazePlotter makes temporally structured gaze data accessible for reproducible, shareable visual analysis. Beyond eye-tracking, the same workflow generalises to any temporally ordered categorical sequence from a compatible CSV input.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.