Public mass shootings are the rarest type of mass murder in the United States. Nevertheless, the media tends to focus on mass murders that appear to be the most newsworthy. The most sensational mass murders are those that have the highest victim count, that target perfect victims, and that occur in a public location. Terrorism and mental health are two separate frames that are often used by the media when reporting a mass shooting event. This creates a lack of accurate reporting that displays a distorted image of mass shootings and affects the public's perception. This study evaluated frames used by the media specifically terrorism and mental health as well as others that came up as a result of this study. Using the Active Shooter Incidents in the United States report, a sample of 75 mass shootings were selected that occurred between 2007 and 2017. This was a qualitative study and consisted of a content analysis of news reports for each of the mass shootings in the sample. Findings revealed several themes that are commonly used by the media when reporting on the mass shooting events. The most common frames found were mental health, terrorism, domestic violence, financial/employment struggles, lack of social skills/loner, political attacks, and criminal/violent backgrounds. Mental health was the most common frame used by media reports to describe motive for the attack. In addition, offenders that were identified as Muslim in the sample were all investigated as having possible terrorism ties. This analysis allowed for an overview of major themes that are commonly present in media reports. The wide sample used in this analysis included the most recent mass shootings in conjunction with the commonly researched mass shootings that have occurred in previous years which supplements the overall literature in this topic.
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Master of Arts (M.A.)
College of Sciences
Length of Campus-only Access
Masters Thesis (Open Access)
Sanchez, Amairini, "An Analysis of Terrorism and Mental Health in Mass Shootings as Perceived by the Media" (2018). Electronic Theses and Dissertations. 5852.
Restricted to the UCF community until May 2018; it will then be open access.