Analysing ocular parameters for web browsing and graph visualization

TL;DR

This paper investigates eye gaze patterns during web browsing and graph visualization, providing new insights and design guidelines to improve user interfaces and data representation in both traditional and virtual environments.

Contribution

It introduces novel techniques for analyzing eye gaze data in web and graph interactions, including a web-based tool and new design guidelines for usability and deception detection.

Findings

Area graphs have fewer gaze clusters and faster response times.

Duration of fixations on deceptive web materials is independent of fixation count.

Web-based eye tracking analysis tool was developed.

Abstract

This paper proposes a set of techniques to investigate eye gaze and fixation patterns while users interact with electronic user interfaces. In particular, two case studies are presented - one on analysing eye gaze while interacting with deceptive materials in web pages and another on analysing graphs in standard computer monitor and virtual reality displays. We analysed spatial and temporal distributions of eye gaze fixations and sequence of eye gaze movements. We used this information to propose new design guidelines to avoid deceptive materials in web and user-friendly representation of data in 2D graphs. In 2D graph study we identified that area graph has lowest number of clusters for user's gaze fixations and lowest average response time. The results of 2D graph study were implemented in virtual and mixed reality environment. Along with this, it was ob-served that the duration while interacting with deceptive materials in web pages is independent of the number of fixations. Furthermore, web-based data visualization tool for analysing eye tracking data from single and multiple users was developed.