Published on in Vol 22, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23725, first published .
Prevalence of Mental Illnesses in Domestic Violence Police Records: Text Mining Study

Prevalence of Mental Illnesses in Domestic Violence Police Records: Text Mining Study

Prevalence of Mental Illnesses in Domestic Violence Police Records: Text Mining Study

Journals

  1. Karystianis G, Cabral R, Adily A, Lukmanjaya W, Schofield P, Buchan I, Nenadic G, Butler T. Mental Illness Concordance Between Hospital Clinical Records and Mentions in Domestic Violence Police Narratives: Data Linkage Study. JMIR Formative Research 2022;6(10):e39373 View
  2. Oatley G. Themes in data mining, big data, and crime analytics. WIREs Data Mining and Knowledge Discovery 2022;12(2) View
  3. Buchner V, Hamm S, Medenica B, Molendijk M. Linguistic Analysis of Online Domestic Violence Testimonies in the Context of COVID-19. SAGE Open 2023;13(1):215824402211461 View
  4. Hui V, Constantino R, Lee Y. Harnessing Machine Learning in Tackling Domestic Violence—An Integrative Review. International Journal of Environmental Research and Public Health 2023;20(6):4984 View
  5. Lovell R, Klingenstein J, Du J, Overman L, Sabo D, Ye X, Flannery D. Using machine learning to assess rape reports: “Signaling” words about victims' credibility that predict investigative and prosecutorial outcomes. Journal of Criminal Justice 2023;88:102107 View
  6. Geurts R, Raaijmakers N, Delsing M, Spapens T, Wientjes J, Willems D, Scholte R. Assessing the Risk of Repeat Victimization Using Structured and Unstructured Police Information. Crime & Delinquency 2023;69(9):1736 View
  7. Lovell R, Klingenstein J, Du J, Overman L, Sabo D, Ye X, Flannery D. Using machine learning to assess rape reports: Sentiment analysis detection of officers' “signaling” about victims' credibility. Journal of Criminal Justice 2023;88:102106 View