Understanding quantified-selfers' practices in collecting and exploring personal data
University of Washington · Microsoft (United States)
Abstract
Researchers have studied how people use self-tracking technologies and discovered a long list of barriers including lack of time and motivation as well as difficulty in data integration and interpretation. Despite the barriers, an increasing number of Quantified-Selfers diligently track many kinds of data about themselves, and some of them share their best practices and mistakes through Meetup talks, blogging, and conferences. In this work, we aim to gain insights from these "extreme users," who have used existing technologies and built their own workarounds to overcome different barriers. We conducted a qualitative and quantitative analysis of 52 video recordings of Quantified Self Meetup talks to understand…
Citation impact
- FWCI
- 76.77
- Percentile
- 100%
- References
- 21
Authors
5Topics & keywords
- Workaround
- Computer science
- Tracking (education)
- Data science
- Context (archaeology)
- Psychology