TY  - CONF
T1  - A Hybrid AI System for Evaluating Media Representation of Violence and Inequality
A1  - Liu, Zhan
A1  - Glassey Balet, Nicole
TI  - 26th International Conference on Web Information Systems Engineering
Y1  - 2025
PB  - Springer Nature
CY  - Marrakech, Morocco
KW  - gender-based violence
KW  - Hybrid AI
KW  - Large Language Models
KW  - Natural Language Processing
KW  - Social bias in media representation
KW  - Web text mining
N2  - Media coverage of gender-based violence plays a critical role in shaping public understanding and policy, yet often perpetuates stereotypes and biases. We present a hybrid AI approach to analyze how French-language media represent gender-based violence. Combining rule-based Natural Language Processing (NLP) with Large Language Models (LLMs), the system applies expert-defined criteria across analytical categories, with each criterion assigned to the most effective method based on empirical performance. This strategy achieves 87.1% overall accuracy, surpassing previous models. GPT-4 led general performance (77.9%), while NLP delivered exceptional results in structural and language-sensitive categories. Our findings demonstrate that combining complementary AI techniques enables near-human accuracy in evaluating media narratives and contributes to advancing web-based text mining for socially relevant media analysis.
ER  -