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Community Issues in American Metropolitan Cities: A Data Mining Case Study
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Author(s): Brooke Sullivan (California State University, Fullerton, CA, USA)and Sinjini Mitra (California State University, Fullerton, CA, USA)
Copyright: 2014
Volume: 16
Issue: 1
Pages: 17
Source title:
Journal of Cases on Information Technology (JCIT)
DOI: 10.4018/jcit.2014010103
PurchaseView on the publisher's website for pricing and purchasing information.
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Abstract
The city of San Francisco in California has 826,000 residents and is growing slowly compared to other large cities in the western United States, facing concerns such as an aging population and flight of families to nearby suburbs. This case study investigates the social and demographic factors that are causing this phenomenon based on data that were collected by San Francisco's city controller's office in its annual survey to residents. By using data analytics, we can predict which residents are likely to move away, and this help us infer which factors of city life and city services contribute to a resident's decision to leave the city. Results of this research indicate that factors like public transportation services, public schools, and personal finances are significant in this regard, which can potentially help the city of San Francisco to prioritize its resources in order to better retain its locals.
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