IDEAS home Printed from https://ideas.repec.org/a/eee/jcjust/v88y2023ics0047235223000776.html
   My bibliography  Save this article

Using machine learning to assess rape reports: Sentiment analysis detection of officers' “signaling” about victims' credibility

Author

Listed:
  • Lovell, Rachel E.
  • Klingenstein, Joanna
  • Du, Jiaxin
  • Overman, Laura
  • Sabo, Danielle
  • Ye, Xinyue
  • Flannery, Daniel J.

Abstract

The first of two articles from a larger study whose aim was to teach a computer to detect innuendo (or signaling) about a victim's credibility in incident reports of rape. This study explored the degree of sentiment and subjectivity in the reports and whether these predicted case progression and outcomes.

Suggested Citation

  • Lovell, Rachel E. & Klingenstein, Joanna & Du, Jiaxin & Overman, Laura & Sabo, Danielle & Ye, Xinyue & Flannery, Daniel J., 2023. "Using machine learning to assess rape reports: Sentiment analysis detection of officers' “signaling” about victims' credibility," Journal of Criminal Justice, Elsevier, vol. 88(C).
    • Handle: RePEc:eee:jcjust:v:88:y:2023:i:c:s0047235223000776
    DOI: 10.1016/j.jcrimjus.2023.102106
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047235223000776
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jcrimjus.2023.102106?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mourtgos, Scott M. & Adams, Ian T., 2019. "The rhetoric of de-policing: Evaluating open-ended survey responses from police officers with machine learning-based structural topic modeling," Journal of Criminal Justice, Elsevier, vol. 64(C), pages 1-1.
    2. Tellis, Katharine M. & Spohn, Cassia C., 2008. "The sexual stratification hypothesis revisited: Testing assumptions about simple versus aggravated rape," Journal of Criminal Justice, Elsevier, vol. 36(3), pages 252-261, July.
    3. Bouffard, Jeffrey A., 2000. "Predicting type of sexual assault case closure from victim, suspect, and case characteristics," Journal of Criminal Justice, Elsevier, vol. 28(6), pages 527-542.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ericka Wentz & Kelsey Keimig, 2019. "Arrest and Referral Decisions in Sexual Assault Cases: The Influence of Police Discretion on Case Attrition," Social Sciences, MDPI, vol. 8(6), pages 1-13, June.
    2. Mourtgos, Scott M. & Adams, Ian T. & Mastracci, Sharon H., 2021. "Improving victim engagement and officer response in rape investigations: A longitudinal assessment of a brief training," Journal of Criminal Justice, Elsevier, vol. 74(C).
    3. Chung, Ji-Bum & Yeon, Dahye & Kim, Min-Kyu, 2023. "Characteristics of victim blaming related to COVID-19 in South Korea," Social Science & Medicine, Elsevier, vol. 320(C).
    4. Campbell, Bradley A. & Menaker, Tasha A. & King, William R., 2015. "The determination of victim credibility by adult and juvenile sexual assault investigators," Journal of Criminal Justice, Elsevier, vol. 43(1), pages 29-39.
    5. Adams, Ian T., 2022. "Modeling Officer Perceptions of Body-worn Cameras: A National Survey," Thesis Commons fnxbg, Center for Open Science.
    6. Michael P Anastario & Monica Adhiambo Onyango & Joan Nyanyuki & Karen Naimer & Rachel Muthoga & Susannah Sirkin & Kelle Barrick & Martijn van Hasselt & Wilson Aruasa & Cynthia Kibet & Grace Omollo, 2014. "Time Series Analysis of Sexual Assault Case Characteristics and the 2007–2008 Period of Post-Election Violence in Kenya," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-6, August.
    7. Adams, Ian T. & McCrain, Joshua & Schiff, Daniel S. & Schiff, Kaylyn Jackson & Mourtgos, Scott M., 2022. "Public Pressure or Peer Influence: What Shapes Police Executives' Views on Civilian Oversight?," SocArXiv mdu96, Center for Open Science.
    8. Adams, Ian T. & Mourtgos, Scott M. & Nix, Justin, 2023. "Turnover in large US policing agencies following the George Floyd protests," Journal of Criminal Justice, Elsevier, vol. 88(C).
    9. Tellis, Katharine M. & Spohn, Cassia C., 2008. "The sexual stratification hypothesis revisited: Testing assumptions about simple versus aggravated rape," Journal of Criminal Justice, Elsevier, vol. 36(3), pages 252-261, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jcjust:v:88:y:2023:i:c:s0047235223000776. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jcrimjus .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.