  Misinformation has disruptive effects on our lives. Many researchers have
looked into means to identify and combat misinformation in text or data
visualization. However, there is still a lack of understanding of how
misinformation can be introduced when text and visualization are combined to
tell data stories, not to mention how to improve the lay public's awareness of
possible misperceptions about facts in narrative visualization. In this paper,
we first analyze where misinformation could possibly be injected into the
production-consumption process of data stories through a literature survey.
Then, as a first step towards combating misinformation in data stories, we
explore possible defensive design methods to enhance the reader's awareness of
information misalignment when data facts are scripted and visualized. More
specifically, we conduct a between-subjects crowdsourcing study to investigate
the impact of two design methods enhancing text-visualization integration,
i.e., explanatory annotation and interactive linking, on users' awareness of
misinformation in data stories. The study results show that although most
participants still can not find misinformation, the two design methods can
significantly lower the perceived credibility of the text or visualizations.
Our work informs the possibility of fighting an infodemic through defensive
design methods.
