GeoAI in social science

Wenwen Li

Chapter 17 in Handbook of Spatial Analysis in the Social Sciences, 2022, pp 291-304 from Edward Elgar Publishing

Abstract: This chapter introduces GeoAI, an emerging field that integrates artificial intelligence, geospatial big data, and high-performance computing for geospatial problem solving. It starts with presenting the unique opportunity GeoAI offers for deepening our understanding of the social systems by serving as an advanced spatial-social analytical technique of big data. Next, the chapter introduces two main threads of GeoAI research methods: the bottom-up data-driven approach, represented by deep learning; and the top-down ontological approach, exemplified by knowledge graph. Two social science use cases are then introduced to demonstrate the applicability and potential of GeoAI approaches to be seamlessly integrated into the social science research framework. These are (1) the application of deep learning for estimating social demographic information at the neighborhood scale; and (2) a disease knowledge graph for spatial and temporal question answering about COVID-19 outbreak. The chapter concludes with a discussion of the remaining challenges and future research directions of GeoAI in social science.

Keywords: Development Studies; Economics and Finance; Environment; Geography; Research Methods; Sociology and Social Policy; Urban and Regional Studies (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.elgaronline.com/view/edcoll/9781789903942/9781789903942.00025.xml (application/pdf)
Our link check indicates that this URL is bad, the error code is: 503 Service Temporarily Unavailable

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:elg:eechap:19110_17

Ordering information: This item can be ordered from
http://www.e-elgar.com

Access Statistics for this chapter

More chapters in Chapters from Edward Elgar Publishing
Bibliographic data for series maintained by Darrel McCalla ().