This article summarizes research that applied algorithm-based technology in an examination of how evidence of officer sentiment toward victims' credibility can influence key procedural decisions down the line; it describes the research results which demonstrated the importance of report language, discussing the relationship between police incident reports and case outcomes as well as implications for best practices.
One of the first steps in a rape investigation is the responding officer’s written report. What the officer includes and how those conclusions are worded can have an impact on the case. In a National Institute of Justice-sponsored study that used cross-disciplinary research, data scientists applied machine learning techniques to nearly two decades’ worth of police reports on rape cases. The data scientists used advanced computational power to support social scientists in a study of how evidence of officer sentiment — meaning opinions and subjectivity — toward victims’ credibility may affect key procedural decisions down the line, such as whether to prosecute a rape case. The study aimed to identify linguistic “signaling” of officers’ views or biases found in their narratives of rape reports.
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