GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalization Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2211.02733
Recent research has demonstrated the capability of behavior signals captured by smartphones and wearables for longitudinal behavior modeling. However, there is a lack of a comprehensive public dataset that serves as an open testbed for fair comparison among algorithms. Moreover, prior studies mainly evaluate algorithms using data from a single population within a short period, without measuring the cross-dataset generalizability of these algorithms. We present the first multi-year passive sensing datasets, containing over 700 user-years and 497 unique users' data collected from mobile and wearable sensors, together with a wide range of well-being metrics. Our datasets can support multiple cross-dataset evaluations of behavior modeling algorithms' generalizability across different users and years. As a starting point, we provide the benchmark results of 18 algorithms on the task of depression detection. Our results indicate that both prior depression detection algorithms and domain generalization techniques show potential but need further research to achieve adequate cross-dataset generalizability. We envision our multi-year datasets can support the ML community in developing generalizable longitudinal behavior modeling algorithms.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2211.02733
- https://arxiv.org/pdf/2211.02733
- OA Status
- green
- Cited By
- 13
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4308610353
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4308610353Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2211.02733Digital Object Identifier
- Title
-
GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling GeneralizationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-11-04Full publication date if available
- Authors
-
Xuhai Xu, Han Zhang, Yasaman S. Sefidgar, Yiyi Ren, Xin Liu, Woosuk Seo, Jennifer Brown, Kevin Kuehn, Mike A. Merrill, Paula S. Nurius, Shwetak Patel, Tim Althoff, Margaret E. Morris, E.A. Riskin, Jennifer Mankoff, Anind K. DeyList of authors in order
- Landing page
-
https://arxiv.org/abs/2211.02733Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2211.02733Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2211.02733Direct OA link when available
- Concepts
-
Generalizability theory, Computer science, Benchmark (surveying), Testbed, Generalization, Wearable computer, Machine learning, Data mining, Task (project management), Artificial intelligence, Statistics, Mathematics, Management, Computer network, Geography, Mathematical analysis, Embedded system, Geodesy, EconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
13Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 4, 2023: 5Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2211.02733 |
| publication_date | 2022-11-04 |
| publication_year | 2022 |
| referenced_works_count | 0 |
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