Harnessing the Power of Machine Learning to Prevent Gender-Based Violence: Using Big Data Techniques to Enhance Research on Violence Against Women
Data on incidents involving violence against women is becoming increasingly accessible, thanks in part to the Violence Against Women Act of 1994 and its reauthorizations. Technology facilitates the sharing of data and qualitative experiences in online forums and social media platforms, which has led to growing demand for analytical tools like data mining and machine learning algorithms to handle these large-scale data sources. This research note provides an overview of the application of big data techniques to research on violence against women and contributes to the discussion on ethical concerns for artificial intelligence in the violence against women research field.
Authors
- Lisa Thompson (ORCID: https://orcid.org/0000-0003-0083-8009)
- Christine Crossland
- Angela Moore (ORCID: https://orcid.org/0009-0007-7700-5781)
Institutions
- Kennesaw State University (US)
- National Institute of Justice (US)
Publication Details
- Journal
- Violence Against Women
- Published
- 2025-02-18
- DOI
- https://doi.org/10.1177/10778012251319701
- Primary Topic
- Crime Patterns and Interventions
- Type
- article
- Field-Weighted Citation Impact
- 0.00