ABSTRACT
Firearm violence continues to be a serious public health problem in the United States. Recent research indicates that victimization and perpetration of firearm violence are exacerbated by social media use and the formation of the “digital street” where youth experiences with violence inform aggressive and threatening content that escalates on social media and leads to retaliation, or Internet banging. Violence prevention and intervention strategies, however, exclude social media as a risk factor, and there are few tools available to community-based organizations for early detection of social media content that may be threatening. Dr. Patton will address this critical gap, present his prototype study in which his research team developed a natural language processing (NLP) system, using a small Twitter dataset from a deceased gang member from Chicago. It integrates qualitative analysis and machine learning to automatically identify Internet banging. He will discuss implications for reducing firearm violence using social media.
BIO
Dr. Desmond Upton Patton is an assistant professor at the Columbia School of Social Work and a Faculty Affiliate of the Social Intervention Group (SIG) and the Data Science Institute. His research utilizes qualitative and computational data collection methods to examine how and why youth and gang violence, trauma, grief and identity are expressed on social media and the real world impact they have on well-being for low-income youth of color.
