Leveraging Text-Chart Links to Support Authoring of Data-Driven Articles with VizFlow

要旨

Data-driven articles --- i.e., articles featuring text and supporting charts --- play a key role in communicating information to the public. New storytelling formats like scrollytelling apply compelling dynamics to these articles to help walk readers through complex insights, but are challenging to craft. In this work, we investigate ways to support authors of data-driven articles using such storytelling forms via a text-chart linking strategy. From formative interviews with 6 authors and an assessment of 43 scrollytelling stories, we built VizFlow, a prototype system that uses text-chart links to support a range of dynamic layouts. We validate our text-chart linking approach via an authoring study with 12 participants using VizFlow, and a reading study with 24 participants comparing versions of the same article with different VizFlow intervention levels. Assessments showed our approach enabled a rapid and expressive authoring experience, and informed key design recommendations for future efforts in the space.

著者
Nicole Sultanum
University of Toronto, Toronto, Ontario, Canada
Fanny Chevalier
University of Toronto, Toronto, Ontario, Canada
Zoya Bylinskii
Adobe Research, Cambridge, Massachusetts, United States
Zhicheng Liu
University of Maryland, College Park, Maryland, United States
DOI

10.1145/3411764.3445354

論文URL

https://doi.org/10.1145/3411764.3445354

動画

会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)

セッション: Designing Effective Visualizations

[A] Paper Room 09, 2021-05-13 17:00:00~2021-05-13 19:00:00 / [B] Paper Room 09, 2021-05-14 01:00:00~2021-05-14 03:00:00 / [C] Paper Room 09, 2021-05-14 09:00:00~2021-05-14 11:00:00
Paper Room 09
13 件の発表
2021-05-13 17:00:00
2021-05-13 19:00:00
日本語まとめ
読み込み中…