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Big Data for Regional Science

Englisch · Fester Einband

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Beschreibung

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Inhaltsverzeichnis

ContentsList of FiguresList of TablesList of ContributorsForeword by Michael Batty1. Introduction Laurie A. Schintler and Zhenhua Chen PART I New Big Data Source in Regional Science2. Opportunities for Retail Data and Their Geographic Integration in Social Science Guy Lansley and Paul Longley 3. Use of Probe Data Generated by Taxis Josep Maria Salanova, Michal Maciejewski, Joschka Bischoff, Miquel Estrada Romeu, Panagiotis Tzenos, and Iraklis Stamos 4. The Emerging Geography of Globalizing Chinese Cities Based on Web-based Information Services Jean-Claude Thill, Jae Soen Son, and Min Chen 5. Using Web Crawled Data for Urban Housing Research Zhenhua Chen 6. Examining Intraurban Migration in the Twin Cities Metropolitan Area using Parcel Data Shipeng Sun 7. Crowdsourcing Street Beauty: Visual Preference Surveys in the Big Data Era Robert Goodspeed and Xiang Yan 8. Public Response to Campus Shootings Using Social Media Xinyue Ye, Zhuo Chen, and Shengwen Li PART II Big Data Integration and Management9. Using Big (Synthetic) Data to Identify Local Housing Market Attributes A.Yair Grinberger and Daniel Felsenstein 10. Using Recurrent Spatio-Temporal Profiles in GPS Panel Data for Enhancing Imputation of Activity Type Tao Feng and Harry J.P. Timmermans 11. Processing Uncertain GPS Trajectory Data for Assessing the Locations of Physical Activity Sungsoon Hwang, Sai Yalla, and Ryan Crews 12. Exploring Digital Technology Industry Clusters Using Administrative and Frontier Data Max Nathan and Anna Rosso 13. The Integration of Internet Data and Census Data for Spatial Analysis in a

Über den Autor / die Autorin

Laurie A. Schintler is a computational social scientist with interests and research activity in the following areas related to Big Data analytics: geocomputation (socio-spatio modelling), transportation, regional science, scientometrics/bibliometrics and network modeling and analysis. She also has expertise on the policy-side of Big Data - specifically, issues related to the digital divide, job automation, workforce education and training and emerging technologies.
Zhenhua Chen is an assistant professor in City and Regional Planning at the Knowlton School of Architecture at The Ohio State University. His research interest includes regional science, big data analytics, risk and resilience, infrastructure planning and policy.

Zusammenfassung

This book provides a comprehensive, multidisciplinary and cutting-edge perspective on big data for regional science. Chapters contain a collection of research notes by experts from all over the world with a wide array of disciplinary backgrounds.

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