Gang Related

Research on gang-related activity increasingly leverages social media data to understand and address community needs. Current efforts focus on developing natural language processing (NLP) techniques, such as machine learning classifiers, to identify individuals involved in or affected by gang violence within online communications, despite challenges posed by non-standard language use. This work aims to improve the efficiency and accuracy of identifying those who could benefit from intervention programs, ultimately contributing to more effective community support and violence prevention strategies. The success of these methods hinges on addressing biases inherent in both data and algorithms to ensure equitable and fair application.