Dataset
Women Framed.
Building multi-regional datasets that help journalists and researchers understand how women are framed in violent events—whether as victims, perpetrators, or bystanders.
Gender Project
DatasetDataset
Women
Framed.
Building multi-regional datasets that help journalists and researchers understand how women are framed in violent events—whether as victims, perpetrators, or bystanders.
Dataset
Women Framed.
Methodology & Scope
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We scraped data directly from five domains: Mada Masr, Al Youm 7, Al Masry Al Youm, Al Wafd, and Al Ahram. After collecting the raw data, we filtered the news stories using a combination of machine-learning algorithms and human review.
This process narrowed more than 100,000 articles down to 455 news stories specifically related to violent crimes either committed against women or perpetrated by women. The analysis used Association Rule mining (ARM) via the Apriori algorithm, applied separately to headlines and full article bodies.
Journalist Training
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Empowering regional voices to understand NLP processing.
Yes, the dataset is accessible to all journalists, researchers, and activists interested in the topic. We prefer that personnel who are interested take a workshop with us to learn what they can about ARM analysis and Apriori before mining.
Open Source Data Access
Open access
Text Size
The dataset is available on Kaggle. We strongly encourage completing a workshop beforehand, but it is not mandatory.