Harnessing the Power of Machine Learning to Prevent Gender-Based Violence

Using Big Data Techniques to Enhance Research on Violence Against Women

Bibliographic Data

ID12438144
AuthorsLisa Thompson (0000-0001-5073-2611, Kennesaw State University, corresponding author), Lisa M Thompson Lee (0000-0003-0083-8009, Kennesaw State University), Angela Moore (0009-0007-7700-5781, National Institute of Justice), Christine Crossland (National Institute of Justice)
Year2025
Volume32
Issue3-4
Pages1023-1036
Publication date2025-02-18
Open AccessYes
TypeARTICLE
VenueViolence Against Women (JOURNAL)
Journal identifiersISSN: 1077-8012 • E-ISSN: 1552-8448
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/10778012251319701
PMID39967290
OpenAlexW4407757114
LanguageEN
References cited41

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

Alternative medicine · Big data · Computer security · Data mining · Data science · Data sharing · Field (mathematics · Internet privacy · Scale (ratio · Social media · World Wide Web · Computer Science · Crime Patterns and Interventions · Cybercrime and Law Enforcement Studies · Medicine · Terrorism, Counterterrorism, and Political Violence

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Open DOI