Work

Using Data Science to Examine Conflict-Related Sexual Violence

Year: 2025

Type: article

Abstract: The lack of data is a major barrier to comprehending conflict-related sexual violence (CRSV). Existing studies indicate a high prevalence of violence but limited documentation. Media are often the first to report CRSV, thus, can data science methods analyze news reports promptly and accurately? We compare manual, machine-learning and Generative AI analysis of thousands of media reports. Five variables can be automatically coded with high accuracy, increasing to over 90% with "chain of thought" prompting. Data science can reveal previously unknown CRSV attributes to inform timely prevention, but it has important limitations that researchers, advocates, and policymakers should be aware of.

Source: Violence Against Women

DOI: 10.1177/10778012251395025

Authors: Sara E. Davies, Jacqui True, Fatemeh Shiri, Yolanda Riveros-Morales

Institutions: Griffith University, Monash University

Language: English

Topic: Gender, Security, and Conflict

Subfield: Gender Studies

Field: Social Sciences

Domain: Social Sciences

SDGs: Peace, justice, and strong institutions, Gender equality

Open Access status: hybrid

Estimated APC paid: $3,650