Gun Violence

Gun violence is a vexing problem in the US that needs little explanation. Yet adequate information and insight are still lacking about ownership and use of firearms, the causes and consequences of gun violence, and the effects of interventions and technological innovations. The sociological context and the implications for health and law enforcement involve a variety of disciplines; and the spectrum of questions that arise affects policymakers at all levels.
Obtaining adequate information and understanding requires high quality data and analyses that can withstand scrutiny by all concerned.

This book provides an overview of reliable data and informative analyses on several important topics in gun violence research. It exposes the opportunities and needs for cutting-edge statistical efforts and engages new statisticians
and data scientists to work across disciplinary lines to help understand and mitigate the effects of gun violence.

Key Features:
• Provides multi-disciplinary perspectives from researchers in criminology, political science, public policy, public health, sociology, and statistics, presenting their latest efforts in gun violence research across disciplinary lines.
• Provides an overview of the state-of-the-art statistical and machine learning methods in gun violence research, including network models, synthetic control methods, point processes models, and neural networks.
• Provides a comprehensive review of data sources, describes the evolution of data quality, and examines the reasons for biases historical data sources.