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Crime Feeds on Legal Activities: Daily Mobility Flows Help to Explain Thieves’ Target Location Choices

Journal of quantitative criminology, 2019-12, Vol.35 (4), p.831-854

2019

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Explaining Theft Using Offenders’ Activity Space Inferred from Residents’ Mobile Phone Data

ISPRS international journal of geo-information, 2024-01, Vol.13 (1), p.8

2024

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Understanding neighborhood income segregation around the clock using mobile phone ambient population data

Humanities & social sciences communications, 2024-12, Vol.11 (1), p.343-13, Article 343

2024

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Unraveling the influence of income-based ambient population heterogeneity on theft spatial patterns: insights from mobile phone big data analysis

Humanities & social sciences communications, 2024-12, Vol.11 (1), p.108-11, Article 108

2024

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Journey-to-Crime Distances of Residential Burglars in China Disentangled: Origin and Destination Effects

ISPRS international journal of geo-information, 2018-08, Vol.7 (8), p.325

2018

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Influence of Varied Ambient Population Distribution on Spatial Pattern of Theft from the Person: The Perspective from Activity Space

ISPRS international journal of geo-information, 2022-12, Vol.11 (12), p.615

2022

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Modeling Spatial Effect in Residential Burglary: A Case Study from ZG City, China

ISPRS international journal of geo-information, 2017-05, Vol.6 (5), p.138

2017

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Educational inequality or educational segregation? The determinants of criminal activities in 288 Chinese cities

Applied geography (Sevenoaks), 2024-01, Vol.162, p.103174, Article 103174

2024

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From Residential Neighborhood to Activity Space: The Effects of Educational Segregation on Crime and Their Moderation by Social Context

Annals of the American Association of Geographers, 2022-11, Vol.112 (8), p.2393-2412

2022

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Causal Effect of Small Businesses on Street Theft: Evidence from a Natural Experiment of the Beijing Cleanup Campaign

Journal of quantitative criminology, 2024-03

2024

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Interpretable machine learning models for crime prediction

Computers, environment and urban systems, 2022-06, Vol.94, p.101789, Article 101789

2022

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Burglars blocked by barriers? The impact of physical and social barriers on residential burglars' target location choices in China

Computers, environment and urban systems, 2021-03, Vol.86, p.101582, Article 101582

2021

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Testing Indicators of Risk Populations for Theft from the Person across Space and Time: The Significance of Mobility and Outdoor Activity

Annals of the American Association of Geographers, 2018-09, Vol.108 (5), p.1370-1388

2018

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The Long-Term Theft Prediction in Beijing Using Machine Learning Algorithms: Comparison and Interpretation

Crime and delinquency, 2023-06

2023

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Residents, Employees and Visitors: Effects of Three Types of Ambient Population on Theft on Weekdays and Weekends in Beijing, China

Journal of quantitative criminology, 2023-06, Vol.39 (2), p.385-423

2023

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Residents' Location-Based Fear of Theft and Their Impact Factors in Guangzhou, China

International journal of environmental research and public health, 2022-12, Vol.20 (1), p.638

2022

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Safety perceptions among African migrants in Guangzhou and Foshan, China

Cities, 2020-04, Vol.99, p.102624, Article 102624

2020

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Using Google Street View imagery to capture micro built environment characteristics in drug places, compared with street robbery

Computers, environment and urban systems, 2021-07, Vol.88, p.101631, Article 101631

2021

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The impact of community residents’ occupational structure on the spatial distribution of different types of crimes

Habitat international, 2021-11, Vol.117, p.102435, Article 102435

2021

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Investigating the diurnal effects of on-street population and streetscape physical environment on street theft crime: A machine learning and negative binomial regression approach using street view images

Applied geography (Sevenoaks), 2024-02, Vol.163, p.103194, Article 103194

2024

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An Analysis of the Correlation between Social Isolation and Crime Suffered by Urban Residents: A Case Study of Guangzhou

Redai dili, 2022-10, Vol.42 (10), p.1752-1760

2022

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Effects of ambient population with different income levels on the spatio-temporal pattern of theft: A study based on mobile phone big data

Cities, 2023-06, Vol.137, p.104331, Article 104331

2023

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Examining the Relationship between Hukou Status, Perceived Neighborhood Conditions, and Fear of Crime in Guangzhou, China

Sustainability, 2020-11, Vol.12 (22), p.9614

2020

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Theft from the person in urban China: assessing the diurnal effects of opportunity and social ecology

Habitat international, 2018-08, Vol.78, p.13-20

2018

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The impact of civil registration-based demographic heterogeneity on community thefts

Habitat international, 2022-11, Vol.129, p.102673, Article 102673

2022

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Crime Feeds on Legal Activities: Daily Mobility Flows Help to Explain Thieves’ Target Location Choices

Explaining Theft Using Offenders’ Activity Space Inferred from Residents’ Mobile Phone Data

Understanding neighborhood income segregation around the clock using mobile phone ambient population data

Unraveling the influence of income-based ambient population heterogeneity on theft spatial patterns: insights from mobile phone big data analysis

Journey-to-Crime Distances of Residential Burglars in China Disentangled: Origin and Destination Effects

Influence of Varied Ambient Population Distribution on Spatial Pattern of Theft from the Person: The Perspective from Activity Space

Modeling Spatial Effect in Residential Burglary: A Case Study from ZG City, China

Educational inequality or educational segregation? The determinants of criminal activities in 288 Chinese cities

From Residential Neighborhood to Activity Space: The Effects of Educational Segregation on Crime and Their Moderation by Social Context

Causal Effect of Small Businesses on Street Theft: Evidence from a Natural Experiment of the Beijing Cleanup Campaign

Interpretable machine learning models for crime prediction

Burglars blocked by barriers? The impact of physical and social barriers on residential burglars' target location choices in China

Testing Indicators of Risk Populations for Theft from the Person across Space and Time: The Significance of Mobility and Outdoor Activity

The Long-Term Theft Prediction in Beijing Using Machine Learning Algorithms: Comparison and Interpretation

Residents, Employees and Visitors: Effects of Three Types of Ambient Population on Theft on Weekdays and Weekends in Beijing, China

Residents' Location-Based Fear of Theft and Their Impact Factors in Guangzhou, China

Safety perceptions among African migrants in Guangzhou and Foshan, China

Using Google Street View imagery to capture micro built environment characteristics in drug places, compared with street robbery

The impact of community residents’ occupational structure on the spatial distribution of different types of crimes

Investigating the diurnal effects of on-street population and streetscape physical environment on street theft crime: A machine learning and negative binomial regression approach using street view images

An Analysis of the Correlation between Social Isolation and Crime Suffered by Urban Residents: A Case Study of Guangzhou

Effects of ambient population with different income levels on the spatio-temporal pattern of theft: A study based on mobile phone big data

Examining the Relationship between Hukou Status, Perceived Neighborhood Conditions, and Fear of Crime in Guangzhou, China

Theft from the person in urban China: assessing the diurnal effects of opportunity and social ecology

The impact of civil registration-based demographic heterogeneity on community thefts

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