Reading Protocol: Understanding what has been Read in Interactive Information Retrieval Tasks

TL;DR

The paper introduces reading protocol software that analyzes eye tracking data at the textual level using HTML structure, enabling large-scale, detailed analysis of gaze behavior in interactive information retrieval experiments.

Contribution

It presents a novel software tool that simplifies and enhances the analysis of eye tracking data in IIR experiments by leveraging web page HTML structure.

Findings

Enables identification of viewed and read content on web pages.

Allows filtering of AOIs based on HTML structure.

Supports comparison of gaze data across multiple users.

Abstract

In Interactive Information Retrieval (IIR) experiments the user's gaze motion on web pages is often recorded with eye tracking. The data is used to analyze gaze behavior or to identify Areas of Interest (AOI) the user has looked at. So far, tools for analyzing eye tracking data have certain limitations in supporting the analysis of gaze behavior in IIR experiments. Experiments often consist of a huge number of different visited web pages. In existing analysis tools the data can only be analyzed in videos or images and AOIs for every single web page have to be specified by hand, in a very time consuming process. In this work, we propose the reading protocol software which breaks eye tracking data down to the textual level by considering the HTML structure of the web pages. This has a lot of advantages for the analyst. First and foremost, it can easily be identified on a large scale what has actually been viewed and read on the stimuli pages by the subjects. Second, the web page structure can be used to filter to AOIs. Third, gaze data of multiple users can be presented on the same page, and fourth, fixation times on text can be exported and further processed in other tools. We present the software, its validation, and example use cases with data from three existing IIR experiments.