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People Like Me
People Like Me
- Source :
- Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 2:1-21
- Publication Year :
- 2018
- Publisher :
- Association for Computing Machinery (ACM), 2018.
-
Abstract
- Increases in data complexity in personal informatics systems require new ways of contextualizing personal data to facilitate meaningful reflection. An emerging approach for providing such context includes augmenting one's personal data with the data of others "like them" to help individuals make sense of their data. However, we do not yet understand how an individual's self-reflection process is affected when the data of others is made available. In this paper, we investigate how people reflect on three types of personal data when presented alongside a large set of aggregated data of multiple cohorts. We conducted personal and cohort data reviews using a subset of participants from a mobile-sensing study that collected physical activity, digital social activity, and perceived stress, from 47 students over three weeks. Participants preferred to use characteristics of the data (e.g., maxima, minima) and graphical presentation (e.g., appearance of trends) along with demographic identities (e.g., age, gender) when relating to cohorts. We further characterize how participants incorporated cohort data into their self-reflection process, and conclude with discussion of the implications for personal informatics systems that leverage the data of "people like me" to enable meaningful reflection.
- Subjects :
- Reflection (computer programming)
Computer Networks and Communications
Process (engineering)
media_common.quotation_subject
05 social sciences
Applied psychology
Aggregate (data warehouse)
020207 software engineering
Context (language use)
02 engineering and technology
Human-Computer Interaction
Presentation
Hardware and Architecture
Cohort
0202 electrical engineering, electronic engineering, information engineering
Leverage (statistics)
0501 psychology and cognitive sciences
Psychology
050107 human factors
media_common
Qualitative research
Subjects
Details
- ISSN :
- 24749567
- Volume :
- 2
- Database :
- OpenAIRE
- Journal :
- Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
- Accession number :
- edsair.doi...........e7069f6030c7cd98ff8e2bd622ac86a2
- Full Text :
- https://doi.org/10.1145/3264917