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 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.
The main aim of thisesearch project is to explore the impact of social cohesion in crime prevention through spatial analysis and use of social media.
The following specific objectives have been outlined:-
- To critically review the literature on the concept of community cohesion and its impacts on crime.
- To use a range of spatial analysis methods to perform a detailed analysis of the relationship between crime and urban community form.
- To investigate the feasibility of using new ‘big’ data sources (such as social media) to explore crime and community cohesion.
- To develop neighbourhood area classification profiles based on a new perception of community cohesion in a range of geographical locations of the study area at community area level.
- To extend understanding of the relationship between crime and community cohesion, based on insights from traditional and new data sources.
Tertiary Education Trust Fund (TETFUND)
Conferences/training courses attended
- Starting your Research Degree - 16/02/2015
- Excel for Research Calculating Data – 27/03/2015
- Introduction to R for Spatial Analysis – 16/03/2015
- Early Careers Researchers Forum – 13th -14th April, 2015
- GISRUK Conference 2015 – 14th – 17th April, 2015
- Power Point Techniques – 23/04/2015
- Time Management for your Research Degree – 13/05/2015
- Effective Poster Presentation - 04/05/2016
- WRDTC Advanced Quantitative Methods Training - 25/06/2016
- WRTDC Social Media Analytics Training - 13/05/2016
- Gulma U.L., Evans A., Heppenstall A. and Malleson N. (2018). Diversity and burglary: Do community differences matter? Transactions in GIS.
- An Analysis of Temporal Rainfall Variability in Argungu Area over the Last Half Climatic Year (1995-2012): Implication on Rainfed Crop Production.
- Remote Sensing and Geographic Information System(GIS) Application to Landsuitability Classification for Irrigation Farming in Argungu Fadama, Kebbi State of Nigeria
- Improvements in Geophysical Surface Soil Assessment and Classification using Modifying Jenny’s Equation of soil forming Factor in Sudan Savannah.
- Spatial Patterns of Tuberclosis Prevalence in Nigeria: A Comparative Analysis of Spatial Autocorrelation Indices
- American Journal of Geographic Information System
- Mapping of Spatial Cases of Tuberculosis in Kebbi State Nigeria (2008-2011). Unpublished paper presented at GISRUK 2015 Conference held at University of Leeds 14th – 17th April, 2015.
- Diversity and Crime in Leeds: Does Community Cohesion Matters?
- GISRUK 2016 Conference Presentation held at University of Greenwich, London 29th March - 1st April, 2016.
- Gulma U.L., Evans A., Heppenstall A. and Malleson N. (2017). Diversity and burglary: Does community cohesion matter?
- 25th GISRUK conference, University of Manchester 18th – 21st April
- Gulma U.L., Evans A., Heppenstall A. and Malleson N. (2016). Diversity and crime in Leeds: Does community cohesion matter?
- 24th GISRUK conference, University of Greenwich 30th March – 1st April
- Big data analytics
- Quantitative modelling
- PhD, University of Leeds
- MSC, GIS, Usmanu Danfodiyo University, Sokoto, Nigeria
- BSc, Geography, Usmanu Danfodiyo University, Sokoto, Nigeria