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Getting Users' Attention in Web Apps in Likable, Minimally Annoying Ways

Published:07 May 2016Publication History

ABSTRACT

Web applications often need to present the user new information in the context of their current activity. Designers rely on a range of UI elements and visual techniques to present the new content to users, such as pop-ups, message icons, and marquees. Web designers need to select which technique to use depending on the centrality of the information and how quickly they need a reaction. However, designers often rely on intuition and anecdotes rather than empirical evidence to drive their decision-making as to which presentation technique to use. This work represents an attempt to quantify these presentation style decisions. We present a large (n=1505) user study that compares 15 visual attention-grabbing techniques with respect to reaction time, noticeability, annoyance, likability, and recall. We suggest glowing shadows and message icons with badges, as well as more possibilities for future work.

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    • Published in

      cover image ACM Conferences
      CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems
      May 2016
      6108 pages
      ISBN:9781450333627
      DOI:10.1145/2858036

      Copyright © 2016 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      New York, NY, United States

      Publication History

      • Published: 7 May 2016

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      Acceptance Rates

      CHI '16 Paper Acceptance Rate565of2,435submissions,23%Overall Acceptance Rate6,199of26,314submissions,24%

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