Authors: Mi Feng, Cheng Deng, Evan Peck, Lane Harrison
Abstract: Designers occasionally add text-based search to visualizations to enable users to quickly identify parts of the visualization they are interested in. Yet precisely how this functionality augments the experience of the visualization as well as the goals of the user remains unknown. To bridge this gap, we contribute a study on text-based search in visualization. We report the results of an experiment on two search-augmented visualizations across 357 online participants, which demonstrate that text-based search influences users' intention to identify personally relevant information in visualizations, and can lead to increased engagement metrics such as more time spent viewing the data elements found using the search box. We then provide a discussion on the broader implications of including search in visualization. We establish a link to existing information seeking taxonomies, showing that search enables users to more diverse information seeking goals with a given visualization.