Type of Publication: Article in Journal

A Deeper Understanding of Visualization–Text Interplay in Geographic Data-driven Stories

Author(s):

Latif, Shahid; Chen, Siming; Beck, Fabian

Title of Journal:

Computer Graphics Forum

Volume (Publication Date):

40 (2021)

Number of Issue:

3

Fulltext:

A Deeper Understanding of Visualization–Text Interplay in Geographic Data-driven Stories (1.10 MB)

Talk associated with this publication:

EuroVis 2021

Recording:

https://youtu.be/BANTOSyWsFI?t=40

Citation:

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Abstract

Data-driven stories comprise of visualizations and a textual narrative. The two representations coexist and complement each other. Although existing research has explored the design strategies and structure of such stories, it remains an open research question how the two representations play together on a detailed level and how they are linked with each other. In this paper, we aim at understanding the fine-grained interplay of text and visualizations in geographic data-driven stories. We focus on geographic content as it often includes complex spatiotemporal data presented as versatile visualizations and rich textual descriptions. We conduct a qualitative empirical study on 22 stories collected from a variety of news media outlets; 10 of the stories report the COVID-19 pandemic, the others cover diverse topics. We investigate the role of every sentence and visualization within the narrative to reveal how they reference each other and interact. Moreover, we explore the positioning and sequence of various parts of the narrative to find patterns that further consolidate the stories. Drawing from the findings, we discuss study implications with respect to best practices and possibilities to automate the report generation.