Using Network Analytics to Improve Targeted Disruption of Police Misconduct

2021 ◽  
pp. 109861112110572
Author(s):  
Timothy I. C. Cubitt
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Law Enforcement ◽  
Network Analysis ◽  
Police Department ◽  
Police Misconduct ◽  
Law Enforcement Agencies ◽  
Targeted Disruption ◽  
Network Analytics ◽  
Practical Implications

Research into police misconduct traditionally considers the correlates and antecedents of misconduct among individual officers, as a means of disruption or prevention. However, more recently, deviance among police has been considered through network perspectives. This study considered 7755 allegations of misconduct accrued by 1495 officers from the Baltimore Police Department between January 2015 to January 2020. A social network analysis was employed to consider the characteristics and differences of misconduct networks between assignments and to identify key officers within these networks. Findings suggested that the misconduct networks of patrol assignments functioned marginally different to investigations or specialist duties. Discrete communities of misconduct were identified within each assignment, including a small number of officers that were particularly important to supporting these networks. This study holds practical implications for the identification and disruption of misconduct networks among law enforcement agencies.

Inter-provincial correlations of agricultural GHG emissions in China based on social network analysis methods

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jiansheng Qu ◽  
Jinyu Han ◽  
Lina Liu ◽  
Li Xu ◽  
Hengji Li ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Temporal Trends ◽  
Ghg Emissions ◽  
Policy Implications ◽  
Content Type ◽  
Ghg Reduction ◽  
And Cluster Analysis ◽  
Practical Implications

PurposeThe purpose of this paper is to explore the heterogeneity and correlations of agricultural greenhouse gas (GHG) emissions among provinces in China, and then policy implications are proposed.Design/methodology/approachAfter agricultural GHG accounting and a pre-analysis of inter-provincial heterogeneity, improved gravity model and the Social Network Analysis (SNA) methods are introduced to construct the network, being carried out from three aspects of the whole network, individual provincial characteristics and cluster analysis.Findings(1) There are significant regional variations in agricultural GHG scale among provinces owing to the layout of agricultural production, and the temporal trends show that the direction and speed of agricultural GHG scale change vary among provinces; (2) In terms of inter-provincial correlations, there exists a complex spatial network of agricultural GHG among provinces, which tends to be more complex, intensive and stable, while the status of the provinces in the network also has gradually become more balanced. All provinces played their respective roles in the four clusters of the network with agricultural layout and comparative advantages, and the distribution has continuously optimized.Practical implicationsThe inter-provincial network characteristics of agricultural GHG emissions and its evolution have practical implications for differentiated and coordinated agricultural GHG reduction policies at the provincial levels.Originality/valueThis paper innovatively study inter-provincial agricultural GHG correlations in China with the SNA methods used to study economic and social connections in the past. There is some originality in the introduction of network theory and application of the SNA methods, which can provide some reference for researches in similar fields.

Mobility and structural change through traumatic organizational events

2014 ◽  
Vol 10 (3) ◽  
pp. 382-408 ◽  
Author(s):  
R. Drew Sellers ◽  
Timothy J. Fogerty ◽  
Larry M. Parker
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Professional Service ◽  
Public Accounting ◽  
Content Type ◽  
The Public ◽  
Arthur Andersen ◽  
Practical Implications

Purpose – This paper aims to, using evidence from a former office of the public accounting firm Arthur Andersen, to study the importance of the relational content and structure of individuals’ social connections as they transitioned to subsequent employment. The paper also examines the maintenance of their social networks through time. Implications for careers in the accounting field are offered. Practicing accountants’ connections with other individuals have often been recognized as an important resource that influences career success. However, these social networks have escaped systematic academic study in accounting. Design/methodology/approach – Social network analysis, built on survey data. Findings – The results show that who one was connected to in a previous employment was more important than one’s overall network position when deciding whether to stay or exit public accounting. However those who exited public accounting did not demonstrate a handicap in maintaining network structures after the disbanding of the firm. Research limitations/implications – This study is limited to firm members, and to a single office of a firm. Social network analysis was used as a research tool for the sociology of public accounting. Practical implications – Implications are for careers in public accounting, and the management of human resources in public accounting is offered. Social implications – The paper has implications for the successfulness of professional service provision in a general sense. Originality/value – Almost a decade of social connection is studied with a method that has not appeared in the discipline but is well regarded in management studies.

scholarly journals Social Network Analysis and Churn Prediction in Telecommunications Using Graph Theory

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 753 ◽  
Author(s):  
Stefan M. Kostić ◽  
Mirjana I. Simić ◽  
Miroljub V. Kostić
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Churn Prediction ◽  
Network Graph ◽  
Network Analytics ◽  
Telecommunications Market ◽  
Market Saturation ◽  
Important Nodes

Due to telecommunications market saturation, it is very important for telco operators to always have fresh insights into their customer’s dynamics. In that regard, social network analytics and its application with graph theory can be very useful. In this paper we analyze a social network that is represented by a large telco network graph and perform clustering of its nodes by studying a broad set of metrics, e.g., node in/out degree, first and second order influence, eigenvector, authority and hub values. This paper demonstrates that it is possible to identify some important nodes in our social network (graph) that are vital regarding churn prediction. We show that if such a node leaves a monitored telco operator, customers that frequently interact with that specific node will be more prone to leave the monitored telco operator network as well; thus, by analyzing existing churn and previous call patterns, we proactively predict new customers that will probably churn. The churn prediction results are quantified by using top decile lift metrics. The proposed method is general enough to be readily adopted in any field where homophilic or friendship connections can be assumed as a potential churn driver.

Sign in / Sign up

Export Citation Format

Share Document