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Using Social Media to Measure Temporal Ambient Population: Does it Help Explain Local Crime Rates?

NCJ Number
253259
Date Published
2019
Length
31 pages
Author(s)
John R. Hipp; Christopher Bates; Moshe Lichman; Padhraic Smyth
Agencies
NIJ-Sponsored
Publication Type
Research (Applied/Empirical), Report (Study/Research), Report (Grant Sponsored), Program/Project Description
Grant Number(s)
2012-R2-CX-0010
Annotation
This study's objective was to use social media (Twitter) data to estimate the population at various locations at different times of day, and then assess whether these estimates help predict the amount of crime during 2-hour time periods over the course of the day.
Abstract
A challenge for studies that assess routine activities theory is accounting for the spatial and temporal confluence of offenders and targets, given that people move about during the daytime and nighttime. The current study addressed these issues by using crime data for 97,428 blocks in the Southern California region, along with geocoded information on tweets in the region over an 8-month period. The results show that this measure of the temporal ambient population helps explain the level of crime in blocks during particular time periods. The use of social media data appear promising for testing various implications of routine activities and crime pattern theories, given their explicit spatial and temporal nature. (publisher abstract modified)
Date Created: July 20, 2021