A Quantitative Method for Analyzing Scan Path Data Obtained by Eye Tracker

Abstract

Scan path is one of the most important metrics measured by eye tracking systems. This paper describes a new method for analyzing scan-path data based on the string-edit method that is popular for correcting human errors made at the input stage. We defined several cost functions for the substitution costs in the string-edit method, and applied the method to the scan-path data we had collected in a series of experiments for studying Web browsing behavior. We demonstrate the usefulness of our method and discuss the appropriate cost functions for the eye-tracking data.