  Recent work has shown that when both the chart and caption emphasize the same
aspects of the data, readers tend to remember the doubly-emphasized features as
takeaways; when there is a mismatch, readers rely on the chart to form
takeaways and can miss information in the caption text. Through a survey of 280
chart-caption pairs in real-world sources (e.g., news media, poll reports,
government reports, academic articles, and Tableau Public), we find that
captions often do not emphasize the same information in practice, which could
limit how effectively readers take away the authors' intended messages.
Motivated by the survey findings, we present EmphasisChecker, an interactive
tool that highlights visually prominent chart features as well as the features
emphasized by the caption text along with any mismatches in the emphasis. The
tool implements a time-series prominent feature detector based on the
Ramer-Douglas-Peucker algorithm and a text reference extractor that identifies
time references and data descriptions in the caption and matches them with
chart data. This information enables authors to compare features emphasized by
these two modalities, quickly see mismatches, and make necessary revisions. A
user study confirms that our tool is both useful and easy to use when authoring
charts and captions.
