title: Finding Waldo: Learning about Users from their Interactions.
abstract: Visual analytics is inherently a collaboration between human and computer. However, in current visual analytics systems, the computer has limited means of knowing about its users and their analysis processes. While existing research has shown that a user's interactions with a system reflect a large amount of the user's reasoning process, there has been limited advancement in developing automated, real-time techniques that mine interactions to learn about the user. In this paper, we demonstrate that we can accurately predict a user's task performance and infer some user personality traits by using machine learning techniques to analyze interaction data. Specifically, we conduct an experiment in which participants perform a visual search task, and apply well-known machine learning algorithms to three encodings of the users' interaction data. We achieve, depending on algorithm and encoding, between 62% and 83% accuracy at predicting whether each user will be fast or slow at completing the task. Beyond predicting performance, we demonstrate that using the same techniques, we can infer aspects of the user's personality factors, including locus of control, extraversion, and neuroticism. Further analyses show that strong results can be attained with limited observation time: in one case 95% of the final accuracy is gained after a quarter of the average task completion time. Overall, our findings show that interactions can provide information to the computer about its human collaborator, and establish a foundation for realizing mixed-initiative visual analytics systems.
authors.forename: Eli T
authors.initials: ET
authors.lastname: Brown
authors.forename: Alvitta
authors.initials: A
authors.lastname: Ottley
authors.forename: Helen
authors.initials: H
authors.lastname: Zhao
authors.lastname: Quan Lin
authors.forename: Richard
authors.initials: R
authors.lastname: Souvenir
authors.forename: Alex
authors.initials: A
authors.lastname: Endert
authors.forename: Remco
authors.initials: R
authors.lastname: Chang
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D003196:Computer Graphics; D003657:Decision Making; D006801:Humans; D007091:Image Processing, Computer-Assisted; D000069550:Machine Learning; D008875:Middle Aged; D010551:Personality; D013647:Task Performance and Analysis; D014584:User-Computer Interface; D055815:Young Adult