为个人信息学中的自我同情设计数据可视化

IF 3.6 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI:10.1145/3631448
Meagan B. Loerakker, Jasmin Niess, Marit Bentvelzen, Paweł W. Woźniak
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引用次数: 0

摘要

可穿戴个人追踪器为促进个人福祉提供了令人兴奋的机会,但也可能助长负面体验。如何设计个人信息学体验,帮助用户以积极的方式构架他们的数据并促进自我同情,仍然是一项挑战。为了探讨这个问题,我们进行了一项研究,比较了用户生成的屏幕时间数据的不同可视化方式。我们考察了数据的积极、中立和消极框架,以及可视化中是否提供了参考点。结果表明,框架技术对反思、反刍和自我同情有显著影响。我们就数据表示的哪些设计特点可以支持个人信息学中的积极体验提出了自己的见解。
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Designing Data Visualisations for Self-Compassion in Personal Informatics
Wearable personal trackers offer exciting opportunities to contribute to one's well-being, but they also can foster negative experiences. It remains a challenge to understand how we can design personal informatics experiences that help users frame their data in a positive manner and foster self-compassion. To explore this, we conducted a study where we compared different visualisations for user-generated screen time data. We examined positive, neutral and negative framings of the data and whether or not a point of reference was provided in a visualisation. The results show that framing techniques have a significant effect on reflection, rumination and self-compassion. We contribute insights into what design features of data representations can support positive experiences in personal informatics.
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来源期刊
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Computer Science-Computer Networks and Communications
CiteScore
9.10
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0.00%
发文量
154
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