In seminal work, Yarbus examined the characteristic scanpaths that result when viewing an image, observing that scanpaths varied significantly depending on the question posed to the observer. While early efforts examining this hypothesis were equivocal, it has since been established that aspects of an observer’s assigned task may be inferred from their gaze. In this thesis we examine two datasets that have not previously been considered involving prediction of task and observer sentiment respectively. The first of these involves predicting general tasks assigned to observers viewing images, and the other predicting subjective ratings recorded after viewing advertisements. The results present interesting observations on task groupings and affective dimensions of images, and the value of various measurements (gaze or image based) in making these predictions. Analysis also demonstrates the importance of how data is partitioned for predictive analysis, and the complementary nature of gaze specific and image derived features. / May 2016