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Using tweets to understand changes in the spatial crime distribution for hockey events in Vancouver
Author(s) -
Ristea Alina,
Andresen Martin A.,
Leitner Michael
Publication year - 2018
Publication title -
the canadian geographer / le géographe canadien
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.35
H-Index - 46
eISSN - 1541-0064
pISSN - 0008-3658
DOI - 10.1111/cag.12463
Subject(s) - crime analysis , geography , cartography , criminology , humanities , sociology , art
Abstract The use of social media data for the spatial analysis of crime patterns during social events has proven to be instructive. This study analyzes the geography of crime considering hockey game days, criminal behaviour, and Twitter activity. Specifically, we consider the relationship between geolocated crime‐related Twitter activity and crime. We analyze six property crime types that are aggregated to the dissemination area base unit in Vancouver, for two hockey seasons through a game and non‐game temporal resolution. Using the same method, geolocated Twitter messages and environmental variables are aggregated to dissemination areas. We employ spatial clustering, dictionary‐based mining for tweets, spatial autocorrelation, and global and local regression models (spatial lag and geographically weighted regression). Findings show an important influence of Twitter data for theft‐from‐vehicle and mischief, mostly on hockey game days. Relationships from the geographically weighted regression models indicate that tweets are a valuable independent variable that can be used in explaining and understanding crime patterns.