By Armita Adily, George Karystianis and Tony Butler

Police attend numerous family and domestic violence (FDV) related events each year and record details of these events as both structured data and unstructured free-text narratives. These descriptive narratives include information about the types of abuse (eg physical, emotional, financial) and the injuries sustained by victims. However, this information is not used in research. In this paper we demonstrate the application of an automated text mining method to identify abuse types and victim injuries in a large corpus of NSW Police Force FDV event narratives (492,393) recorded between January 2005 and December 2016. Specific types of abuse and victim injuries were identified in 71.3 percent and 35.9 percent of FDV event narratives respectively. The most commonly identified abuse types mentioned in the narratives were non-physical (55.4%). Our study supports the application of text mining for use in FDV research and monitoring.

Trends & issues in crime and criminal justice no. 630. Canberra: Australian Institute of Criminology. 2021. 12p.

By Armita Adily, George Karystianis and Tony Butler

In this paper, we describe the feasibility of using a text-mining method to generate new insights relating to family and domestic violence (FDV) from free-text police event narratives. Despite the rich descriptive content of the event narratives regarding the context and individuals involved in FDV events, the police narratives are untapped as a source of data to generate research evidence. We used text mining to automatically identify mentions of mental disorders for both persons of interest (POIs) and victims of FDV in 492,393 police event narratives created between January 2005 and December 2016. Mentions of mental disorders for both POIs and victims were identified in nearly 15.8 percent (77,995) of all FDV events. Of all events with mentions of mental disorder, 76.9 percent (60,032) and 16.4 percent (12,852) were related to either POIs or victims, respectively. The next step will be to use actual diagnoses from NSW Health records to determine concordance between the two data sources. We will also use text mining to extract information about the context of FDV events among key at-risk groups.

Trends & issues in crime and criminal justice no. 629. Canberra: Australian Institute of Criminology. 2021. 16p.

By Kristy E. Williams, U.S. Government Accountability Office

Domestic and child abuse can result in devastating consequences for military service members and their families. It also can reduce mission readiness. In fiscal year 2023, DOD recorded 26,978 reports of domestic and child abuse incidents, of which 14,110 met the DOD definition of abuse. House Report 117-397 includes a provision for GAO to review the policies and regulations governing IDCs and the use of decision notification letters. This report (1) describes how military commanders, abuse victims, and alleged abusers may use IDC decisions; and (2) assesses the extent to which the military services have established processes to notify commanders, abuse victims, and alleged abusers of IDC decisions. GAO conducted site visits at four military installations; analyzed random samples of IDC notifications and incident case logs; reviewed DOD and military service guidance; and interviewed DOD, military service, and civilian officials. What GAO Recommends GAO recommends DOD clarify its guidance and expectations on incident determination notification methods and content based on its identification and analysis of associated risks. DOD concurred with GAO’s recommendation.    

Washington, DC: U.S. Government Accountability Office, 2024. 49p.