  It is common to compare state changes of multiple data items and identify
which data items have changed more in various applications (e.g., annual GDP
growth of different countries and daily increase of new COVID-19 cases in
different regions). Grouped bar charts and slope graphs can visualize both
state changes and their initial and final states of multiple data items, and
are thus widely used for state change comparison. But they leverage implicit
bar differences or line slopes to indicate state changes, which has been proven
less effective for visual comparison. Both visualizations also suffer from
visual scalability issues when an increasing number of data items need to be
compared. This paper fills the research gap by proposing a novel radial
visualization called Intercept Graph to facilitate visual comparison of
multiple state changes. It consists of inner and outer axes, and leverages the
lengths of line segments intercepted by the inner axis to explicitly encode the
state changes. Users can interactively adjust the inner axis to filter large
changes of their interest and magnify the difference of relatively-similar
state changes, enhancing its visual scalability and comparison accuracy. We
extensively evaluate the Intercept Graph in comparison with baseline methods
through two usage scenarios, quantitative metric evaluations, and well-designed
crowdsourcing user studies with 50 participants. Our results demonstrate the
usefulness and effectiveness of the Intercept Graph.
