Faces and Viewing Behavior: An Exploratory Investigation

Abstract

User experience is becoming increasingly important in gaining a competitive advantage in the marketplace. One way to improve user experience is by including images of faces. People are drawn to faces because paying attention to faces has played a significant role in human evolution. Hence, areas on a web page that typically receive less attention from users, such as the right side or below the fold, may benefit from the inclusion of images of faces. Although faces may be useful in attracting attention to particular places on a web page, they may also distract attention from key information. To test this possibility, we conducted two eye tracking studies in which images of faces were placed on areas of a web page that are shown to receive less attention. The results indicated that faces did not increase the number of people who viewed the areas where the faces were located, but that faces affected fixation patterns on these areas. Our results also showed that faces located above the fold of the web page negatively affected the performance of those who were completing tasks.

Eye Tracking and Web Experience

“…When human images are present on websites, viewers tend to focus mainly on faces. Given the importance of faces in non-verbal communication, this viewing pattern is not surprising (Djamasbi, Siegel, & Tullis, 2012b). Heat maps in Figure 10 display a few eye tracking examples of this phenomenon (note the red spots on faces).…”

“…Grounded in the argument that attention to faces has been important in humans' survival and well-being, a recent eye tracking study used heat maps to show that faces, more than other images, can draw users' attention (Djamasbi et al, 2012b). Because of this, faces on a webpage can have the unintended consequence of diverting attention away from information that is placed adjacent to them.…”

Complacency and Intentionality in IT Use and Continuance

“…Therefore, we believe it is not likely that the participants' view times decreased as a result of learning how to use the decision aid over time because they were already familiar with the aid before the experiment began. Second, even though the decision aid layout remained the same, we provided the participants with different information content for each trial (such as different headlines and comments that they had to consider rather than with closing prices that they could compare), which is a common procedure for reducing the possibility of learning effects (e.g., Adipat, Zhang, & Zhou, 2011;Djamasbi et al, 2012). Third, attributing the decrease in view times to learning effects assumes that the participants learned how to use the decision aid to evaluate stocks faster over time.…”

“…Other researchers have used similar eye trackers from the same manufacturer to examine individuals' information browsing behaviors, such as reading expert opinions on a webpage (Djamasbi, Siegel, & Tullis, 2012) or simply browsing e-commerce sites to select products (Sheng & Joginapelly, 2012). We collected two types of data via the eye tracker: view time and fixation count.…”

Real-time Prediction of User Performance based on Pupillary Assessment via Eye-Tracking

“…Using our cost-efficient and physiology-based method, one can empirically investigate the relationships between mental effort and other important IS constructs such as perceived ease of use in a much more sophisticated manner (Dimoka et al, 2011;Dimoka et al, 2012;de Guinea et al, 2014). Furthermore, our approach may complement other eye-tracking approaches such as gaze-fixation analysis in order to improve user experience (Djamasbi, Siegel, & Tullis, 2012;Sheng & Joginapelly, 2012;Eckhardt et al, 2013;Djamasbi, 2014), a triangulation that may also help to better explain the construct of mental effort itself since, until now, research has not defined mental effort and its derivatives well psychometrically (Xie & Salvendy, 2000;Dunaway & Steelman 2013, Matthews, Reinerman-Jones, Barber, & Abich, 2015.…”