Vizdat: A Technology Probe to Understand the Space of Discussion Around Data Visualization on Reddit

Author:

Almahmoud Jumana1ORCID,Karger David R.1ORCID

Affiliation:

1. Massachusetts Institute of Technology, Cambridge, MA, USA

Abstract

Visualizations play a considerable role in explaining trends or providing evidence when consuming data online. Whether those visualizations are shared on news outlets or social networks, platforms usually allow readers to discuss their stories in comments sections. For the scope of this work, we studied the online communityr/dataisbeautiful on Reddit. We found that chart creators were using a variety of authoring tools to share their content. Readers of these posts,commenters, used text mainly to discuss and critique the visual content. We noticed a need for a richer mode of communication that would show instead of telling authors what to do. Based on our findings, we introducedVizdat, a lightweight tool and extension to allow users to visualize and reproduce charts in the comments sections of data stories. We usedVizdat as atechnology probe with 11 Reddit users to create data visualization and discuss charts onr/dataisbeautiful. During the four-week field deployment period, we observed howVizdat was used and interviewed the participants. We found thatcommenters saw value in accessing the visualization specifications throughVizdat and used those charts to structure their replies with richer modalities. As a result, visualizationauthors appreciated the feedback and less toxic discussion provided through comments embedded with modified versions of their charts. In our paper, we share these findings and other insights to understand the dynamics of forum discussion around charts.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

Reference38 articles.

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3. 2019. Library for inferring which type of data visualization can be rendered from a JSON dataset and with which data field(s): Vizzuality/jiminy. https://github.com/Vizzuality/jiminy original-date: 2016-03-02T10:22:07Z. 2019. Library for inferring which type of data visualization can be rendered from a JSON dataset and with which data field(s): Vizzuality/jiminy. https://github.com/Vizzuality/jiminy original-date: 2016-03-02T10:22:07Z.

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