Using tweets to understand changes in the spatial crime distribution for hockey events in Vancouver
Dados Bibliográficos
| ID | 8423936 |
|---|---|
| Autores | Alina Ristea (0000-0003-2682-1416, University of Salzburg, autor correspondente), M A Andresen (0000-0002-4767-7276, Simon Fraser University), Michael Leitner (0000-0002-1204-0822, Louisiana State University) |
| Ano | 2018 |
| Volume | 62 |
| Fascículo | 3 |
| Páginas | 338-351 |
| Data de publicação | 2018-09-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Canadian Geographies / Géographies canadiennes (JOURNAL) |
| Identificadores do periódico | ISSN: 0008-3658 • E-ISSN: 1541-0064 |
| Editora | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/cag.12463 |
| PMID | 31031410 |
| OpenAlex | W2802115700 |
| Idioma | EN |
| Citações recebidas | 9 |
| Referências citadas | 35 |
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
Art · Cartography · Crime analysis · Criminology · Geography · Humanities · Sociology · Crime Patterns and Interventions · Data-Driven Disease Surveillance · Spatial and Panel Data Analysis
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| Obras citantes distintas | 9 |
|---|---|
| Citações por ano | 1,5 |
| Intervalo de citações | 2020 - 2025 (6) |
| Velocidade de citação | recent |
| Altamente citado | Não |
| Tipos de citação | Neutras: 9 |