Design Techniques for COVID-19 Story Maps: A Quantitative Content Analysis

ABSTRACT

Story maps have emerged as a popular storytelling device in recent years with cartographers and journalists leveraging geospatial web technologies to create unique spatial narratives. However, empirical research analyzing the design of story maps remains limited. Two recently proposed design frameworks provide promising avenues to characterize story maps in terms of elements of vivid cartography and techniques of map-based storytelling. In this article, I conducted a quantitative content analysis on 117 story maps of COVID-19 to operationalize map-based storytelling and vividness frameworks and to identify common design traits in contemporary story maps. My findings indicated that most story maps are longform infographics that use scrolling to advance the narrative. Stories applied a variety of attention, dosing, and mood techniques to enrich the storytelling experience. Story maps were primarily vivid through their use of color and novelty. Overall, most story maps utilized only a fraction of the map-based storytelling framework techniques. This research also demonstrated that it is challenging to analyze story maps based on these frameworks. Finally, this article improves the frameworks by proposing two new story map techniques and suggesting avenues of refinement.

KEYWORDS:

• Visual storytelling
• data journalism
• story maps
• cartographic design
• health communication
• content analysis

Acknowledgement

The author would like to thank Lily Houtman, Chris Archuleta, and Jake Steinberg for their assistance in the coding process. The author also wishes to thank Anthony Robinson, Cindy Brewer, and Helen Greatrex for their feedback on the many drafts of this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability

The data that support the findings of this study are openly available at https://doi.org/10.6084/m9.figshare.20134499.v1. The appendices referenced in this study are hosted as supplementary material at https://doi.org/10.6084/m9.figshare.20134817.v1.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15230406.2022.2102077

Additional information

Funding

The work was supported by the Wisconsin Land Information Association Foundation, Inc.; United States Geospatial Intelligence Foundation; Department of Geography, The Pennsylvania State University.