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The Impact of Community Cohesion on Crime

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The Impact of Community Cohesion on Crime The Impact of Community Cohesion on Crime Usman Lawal Gulma Submitted in accordance with the requirements for the degree of Doctor of Philosophy The University of Leeds School of Geography Centre for Spatial Analysis and Policy September, 2018 The candidate confirms that the work submitted is his/her own and that appropriate credit has been given where reference has been made to the work of others. This copy has been supplied on the understanding that it is copyright material and that no quotation from the thesis may be published without proper acknowledgement. Academic Acknowledgements I would like to thank the UK Data Service: Census Support for providing the Census 2011 statistics that were used in this research. I would also like thank the United Kingdom Boundary Outline and Reference Database for Educational and Research Study (UKBORDERS) for the outline maps used. I also thank Professor John Stillwell for permitting me to reproduce his work on Leeds Community Areas in this research. Finally, I would like to thank the West Yorkshire Police for providing their publicly available data through the data.police.uk website. i Acknowledgements All praise is due to almighty Allah the Most Gracious and the Most Merciful for seeing me through to a successful completion of this research. I would like to thank my supervisors: Professor Alison Heppenstall, Dr Andrew Evans and Dr Nick Malleson, for their untiring and invaluable contribution throughout the duration of the research. Indeed, I am greatly indebted for all your support and expertise without which this research would not have been a success. I would also like to thank the members of research support group (RSG) in the person of Professor John Stillwell and Dr Andy Newing for their help. My profound gratitude goes to the Tertiary Education Trust Fund (TETFUND) for funding the research project. I would also like to thank the School of Geography for providing me with an additional funding towards the completion of the research. I am also grateful to my office colleagues and all other persons too numerous to be mention here who have made my stay in Leeds a memorable one. I would like to extend my sincere gratitude to my wife and children, the entire family of Late Tafida Lawal Gulma and particularly my mum for their prayers and continuous moral encouragement throughout the duration of this research. Finally, I would like to dedicate this work in memory of my late dad who, as Allah Has wished, could not be around to celebrate this achievement with me. ii Abstract Community cohesion generally acts to increase the safety of communities by increasing informal guardianship, and enhancing the work of formal crime prevention organisations. Understanding the dynamics of local social interactions is essential for community building. However, community cohesion is difficult to empirically quantify, because there are no obvious and direct indicators of community cohesion collected at population levels within official datasets. A potentially more promising alternative for estimating community cohesion is through the use of data from social media. Social media offers an opportunity for exploring networks of social interactions in a local community. This research will use social media data to explore the impact of community cohesion on crime. Sentiment analysis of tweets can help to uncover patterns of community mood in different areas. Modelling of community engagement on Facebook is useful for understanding patterns of social interactions and the strength of social networks in local communities. The central contribution of this thesis is the use of new metrics that estimate popularity, commitment and virality known as the PCV indicators for quantifying community cohesion on social media. These metrics, combined with diversity statistics constructed from “traditional” Census data, provide a better correlate of community cohesion and crime. To demonstrate the viability of this novel method for estimating the impact of community cohesion, a model of community engagement and burglary rates is constructed using Leeds community areas as an example. By examining the diversity of different community areas and strength of their social networks, from traditional and new data sources; it was found that stability and strong social media engagement in a local area are associated with lower burglary rates. The proposed new method can provide a better alternative for estimating community cohesion and its impact on crime. It is recommended that policy planning for resource allocation and community building needs to consider social structure and social networks in different communities. iii Publication and Conferences The following table presents peer reviewed paper publication and conference presentations from the thesis. Peer-reviewed published paper Gulma U.L., Evans A., Heppenstall A. Part of the work in Chapter 5 of the thesis and Malleson N. (2018). Diversity and (see Appendix B) burglary: Do community differences matter? Transactions in GIS. DOI: 1111/tgis.12511 Peer-reviewed conference presentations Gulma U.L., Evans A., Heppenstall A. 25th GISRUK conference, University of and Malleson N. (2017). Diversity and Manchester 18th – 21st April burglary: Does community cohesion matter? Gulma U.L., Evans A., Heppenstall A. 24th GISRUK conference, University of and Malleson N. (2016). Diversity and Greenwich 30th March – 1st April crime in Leeds: Does community cohesion matter? iv Table of Contents List of Figures, Tables and Abbreviations Abstract ........................................................................................................................... iii Table of Contents ............................................................................................................ v Chapter 1 : Introduction ................................................................................................... 1 1.1 Background of the Study ....................................................................................... 1 1.1.1 Problem Statement ......................................................................................... 2 1.2 Aim and Objectives ................................................................................................ 3 1.2.1 Justification for the Study ................................................................................ 4 1.2.2 Significance of the Study ................................................................................. 5 1.2.3 Defining Community in the Context of Crime .................................................. 5 1.3 Thesis Structure ..................................................................................................... 6 Chapter 2 : Concept of Community Cohesion and Crime: A Literature Review .............. 9 2.1 Introduction ............................................................................................................ 9 2.2 Defining the Concept of Community Cohesion ...................................................... 9 2.3 Community Cohesion and Crime ......................................................................... 10 2.4 Importance of Social Capital on Crime ................................................................ 13 2.5 Determinants of Social Capital in Relation to Crime ............................................ 15 2.5.1 Age, Social Capital and Crime ...................................................................... 18 2.5.2 Gender, Social Capital and Crime ................................................................. 19 2.5.3 Internet Usage and Social Capital ................................................................. 21 2.5.4 Online Membership and Social Capital ......................................................... 22 2.5.5 Participation in Community Activities, Social Capital and Crime ................... 24 2.5.6 Participation in Election, Social Capital and Crime ........................................ 25 2.5.7 Heterogeneity, Social Capital and Crime ...................................................... 26 2.5.8 Education, Social Capital and Crime ............................................................. 27 2.5.9 Length of Residence, Social Capital and Crime ............................................ 28 2.5.10 Deprivation, Social Capital and Crime ......................................................... 29 2.6 Collective Efficacy and Crime .............................................................................. 30 v 2.6.1 Measurement of Collective Efficacy on Crime ............................................... 30 2.7 Weaknesses of Previous Studies ........................................................................ 32 2.8 Theoretical Framework ........................................................................................ 33 2.8.1 Social Disorganisation Theory ....................................................................... 33 2.8.2 Routine Activity Theory ................................................................................. 35 2.9 Concluding Remarks ........................................................................................... 37 Chapter 3 : Traditional Methods of Modelling Urban Social Systems and Crime .......... 38 3.1 Introduction .......................................................................................................... 38 3.2 Research Methodology ........................................................................................ 38 3.3 Study Area
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