Designing narratives and data visuals in comic form for social influence in climate action

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

4 Scopus Citations
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Original languageEnglish
Article number893181
Journal / PublicationFrontiers in Psychology
Volume13
Online published27 Sept 2022
Publication statusPublished - 2022

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Abstract

Climate change is difficult to connect with personally, because people only regard the phenomenon as important if it becomes a perceived threat to themselves. Arguments like statistics and policy debates are extrinsic motivators, which do not necessarily align people’s own intrinsic motives with those of climate action. Instead, narratives and visual communication can influence viewers implicitly by the way they show and reinforce actions and thoughts that align with climate action. In this design study, we used comics created for human-level climate change influence to promote ideas like future-based thinking, sharing of responsibility, and caring for each other. We also created data visuals that illustrate future consequences of climate change for the purpose of averting negative alternative realities. To see whether our design can affect audience perception of climate change on the human level of goals and desires, we showed the comics to readers unfamiliar with the themes of the stories, presenting them as manga about characters and situations. The survey showed that data stories can affect the way naive readers interpret narratives to align with pro-climate attitudes such as sharing and future-vision, and that readers are focused on the human-level of the data and story as opposed to the physical resource level. Speculative fiction and data visuals provide a potentially effective way to influence individuals’ climate change attitudes by showing alternative realities and attributes of collective responsibility and planning-for-the-future as data stories.

Research Area(s)

  • design fiction, data comics, climate action, data narratives, data visuals

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