Eye Tracking Scanpath Analysis Techniques on Web Pages: A Survey, Evaluation and Comparison

Eraslan, Sukru
Yesilada, Yeliz
Harper, Simon
Eye tracking has commonly been used to investigate how users interact with web pages, with the goal of improving their usability. This article comprehensively revisits the techniques that could be applicable to eye tracking data for analysing user scanpaths on web pages. It also uses a third-party eye tracking study to compare these techniques. This allows researchers to recognise existing techniques for their goals, understand how they work and know their strengths and limitations so that they can make an efficient choice for their studies. These techniques can mainly be used for calculating similarities/dissimilarities between scanpaths, computing transition probabilities between web page elements, detecting patterns in scanpaths and identifying common scanpaths. The scanpath analysis techniques are classified into four groups by their goals so that researchers can directly focus on the appropriate techniques for a sequential analysis of user scanpaths on web pages. This article also suggests dealing with the limitations of these techniques by pre-processing eye tracking data, considering cognitive processing and addressing their reductionist approach.


Trends in Eye Tracking Scanpaths: Segmentation Effect?
Eraslan, Sukru; Yesilada, Yeliz; Harper, Simon (2016-07-13)
Eye tracking has been widely used to investigate user interactions with the Web to improve user experience. In our previous work, we developed an algorithm called Scanpath Trend Analysis (STA) that analyses eye movement sequences (i.e., scanpaths) of multiple users on a web page and identifies their most commonly followed path in terms of the visual elements of the page. These visual elements are mainly the segments of a page generated by automated segmentation approaches. In our previous work, we also show...
Predicting Trending Elements on Web Pages Using Eye-Tracking Data
Shekh Khalil , Naziha; Yeşilada, Yeliz; Eraslan, Şükrü; Computer Engineering (2022-8-31)
Eye-tracking data can be used to understand how users interact with web pages and such understanding can be facilitated for different purposes, for example, it can be used to support better accessibility for disabled users or better usability for all users. However, understanding the sequential behavior of a group of users is challenging from eye-tracking data because individual eye movement sequences, i.e. scanpaths, tend to be complicated and different from each other. Previous work proposes an algorithm ...
Eye Tracking Scanpath Analysis on Web Pages: How Many Users?
Eraslan, Sukru; Yesilada, Yeliz; Harper, Simon (2016-03-17)
The number of users required for usability studies has been a controversial issue over 30 years. Some researchers suggest a certain number of users to be included in these studies. However, they do not focus on eye tracking studies for analysing eye movement sequences of users (i.e., scanpaths) on web pages. We investigate the effects of the number of users on scanpath analysis with our algorithm that was designed for identifying the most commonly followed path by multiple users. Our experimental results su...
Scanpath Trend Analysis on Web Pages: Clustering Eye Tracking Scanpaths
Eraslan, Sukru; Yesilada, Yeliz; Harper, Simon (Association for Computing Machinery (ACM), 2016-12-01)
Eye tracking studies have widely been used in improving the design and usability of web pages and in the research of understanding how users navigate them. However, there is limited research in clustering users' eye movement sequences (i.e., scanpaths) on web pages to identify a general direction they follow. Existing research tends to be reductionist, which means that the resulting path is so short that it is not useful. Moreover, there is little work on correlating users' scanpaths with visual elements of...
Mining eyetracking data to characterise users and theirpatterns of use
Öder, Melih; Betin Can, Aysu; Department of Information Systems (2019)
Eye tracking studies typically collect an enormous amount of data that encodes a lot of information about the users’ behavior and characteristics on the web. However, there are not many studies that mine such data to learn and discover user characteristics and profiles. The main goal of this study is to mine eye tracking data by machine learning methods to create data models which characterise users and predict their characteristics, in particular, familiarity and gender. Detecting users’ characteristics can...
Citation Formats
S. Eraslan, Y. Yesilada, and S. Harper, “Eye Tracking Scanpath Analysis Techniques on Web Pages: A Survey, Evaluation and Comparison,” JOURNAL OF EYE MOVEMENT RESEARCH, pp. 0–0, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66399.