Anzeige
Erschienen in:
2012 | OriginalPaper | Buchkapitel
Attention and Selection in Online Choice Tasks
verfasst von : Vidhya Navalpakkam, Ravi Kumar, Lihong Li, D. Sivakumar
Erschienen in: User Modeling, Adaptation, and Personalization
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The task of selecting one among several items in a visual display is extremely common in daily life and is executed billions of times every day on the Web. Attention is vital for selection, but the end-to-end process of what draws and sustains attention, and how that influences selection, remains poorly understood. We study this in a complex multi-item selection setting, where participants selected one among eight news articles presented in a grid layout on a screen. By varying the position, saliency, and topic of the news items, we identify the relative importance of these visual and semantic factors in attention and selection. We present a simple model of attention that predicts many key features such as attention shifts and dwell time per item. Potential applications of our findings include optimizing visual displays to drive user attention.