Activity Spaces and Big Data Sources in Segregation Research: A Methodological Review Article Swipe
Kerli Müürisepp
,
Olle Järv
,
Tiit Tammaru
,
Tuuli Toivonen
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3389/frsc.2022.861640
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3389/frsc.2022.861640
The activity space approach is increasingly mobilized in spatial segregation research to broaden its scope from residential neighborhoods to other socio-spatial contexts of people. Activity space segregation research is an emerging field, characterized by quick adaptation of novel data sources and interdisciplinary methodologies. In this article, we present a methodological review of activity space segregation research by identifying approaches, methods and data sources applied. First, our review highlights that the activity space approach enables segregation to be studied from the perspectives of people, places and mobility flows. Second, the results reveal that both traditional data sources and novel big data sources are valuable for studying activity space segregation. While traditional sources provide rich background information on people for examining the social dimension of segregation, big data sources bring opportunities to address temporality, and increase the spatial extent and resolution of analysis. Hence, big data sources have an important role in mediating the conceptual change from a residential neighborhood-based to an activity space-based approach to segregation. Still, scholars should address carefully the challenges and uncertainties that big data entail for segregation studies. Finally, we propose a framework for a three-step methodological workflow for activity space segregation analysis, and outline future research avenues to move toward more conceptual clarity, integrated analysis framework and methodological rigor.
Related Topics
Concepts
Big data
Data science
Space (punctuation)
Scope (computer science)
CLARITY
Field (mathematics)
Temporality
Dimension (graph theory)
Workflow
Adaptation (eye)
Conceptual framework
Computer science
Sociology
Epistemology
Social science
Data mining
Psychology
Pure mathematics
Database
Chemistry
Biochemistry
Programming language
Neuroscience
Philosophy
Mathematics
Operating system
Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.3389/frsc.2022.861640
- OA Status
- gold
- Cited By
- 24
- References
- 72
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4281286425
All OpenAlex metadata
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https://openalex.org/W4281286425Canonical identifier for this work in OpenAlex
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https://doi.org/10.3389/frsc.2022.861640Digital Object Identifier
- Title
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Activity Spaces and Big Data Sources in Segregation Research: A Methodological ReviewWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-05-23Full publication date if available
- Authors
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Kerli Müürisepp, Olle Järv, Tiit Tammaru, Tuuli ToivonenList of authors in order
- Landing page
-
https://doi.org/10.3389/frsc.2022.861640Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.3389/frsc.2022.861640Direct OA link when available
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Big data, Data science, Space (punctuation), Scope (computer science), CLARITY, Field (mathematics), Temporality, Dimension (graph theory), Workflow, Adaptation (eye), Conceptual framework, Computer science, Sociology, Epistemology, Social science, Data mining, Psychology, Pure mathematics, Database, Chemistry, Biochemistry, Programming language, Neuroscience, Philosophy, Mathematics, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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24Total citation count in OpenAlex
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2025: 10, 2024: 8, 2023: 5, 2022: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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