Brianna White

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Jul 30, 2019
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Studious Asians, sassy yet helpless women and greedy shopkeepers: These tired stereotypes of literature and film not only often offend the people they caricature, but can drag down what might otherwise have been a compelling narrative.
Researchers at the University of Maryland’s Human-Computer Interaction Lab are working to combat these clichés with the creation of DramatVis Personae (DVP), a web-based visual analytics system powered by artificial intelligence that helps writers identify stereotypes they might be unwittingly giving fictional form among their cast of characters (or dramatis personae).
“DVP is designed to integrate smoothly with the writer’s own creative process,” said Naimul Hoque, a third-year doctoral student in information studies who recently presented DVP at the annual ACM SIGCHI Conference on Designing Interactive Systems.
It allows them to analyze existing literature for research, upload their written content as it becomes available, or even write in the tool itself, and then have its text analytics and visualizations update in real time, he said.
Continue reading: https://today.umd.edu/how-ai-could-help-writers-spot-stereotypes
 

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