Who ‘Tweets’ Where and When, and How Does it Help Understand Crime Rates at Places? Measuring the Presence of Tourists and Commuters in Ambient Populations-Reference-Cited by-同舟云学术

Who ‘Tweets’ Where and When, and How Does it Help Understand Crime Rates at Places? Measuring the Presence of Tourists and Commuters in Ambient Populations

Published:2021-01-28 Issue:2 Volume:37 Page:333-359
ISSN:0748-4518
Container-title:Journal of Quantitative Criminology
language:en
Short-container-title:J Quant Criminol

Author:

Tucker Riley^ORCID,O’Brien Daniel T.,Ciomek Alexandra,Castro Edgar,Wang Qi,Phillips Nolan Edward

Publisher

Springer Science and Business Media LLC

Subject

Law,Pathology and Forensic Medicine

Link

https://link.springer.com/content/pdf/10.1007/s10940-020-09487-1.pdf

Reference64 articles.

1. Albanese JS (1985) The effect of casino gambling on crime. Fed Probat 49:39–44

2. Andresen MA (2006) Crime measures and the spatial analysis of criminal activity. Br J Criminol 46(2):258–285

3. Andresen MA (2010) Diurnal movements and the ambient population: an application tomunicipal-level crime rate calculations. Canad J Criminol Crim Just 52(1):97–109

4. Andresen MA (2011) The ambient population and crime analysis. Prof Geograph 63(2):193–212

5. Andresen MA, Jenion GW (2010) Ambient populations and the calculation of crime rates and risk. Secur J 23(2):114–133

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