In a first-of-its-kind effort, social media researchers from 91制片厂's College of Computing & Informatics (CCI), Vanderbilt University, Georgia Institute of Technology and Boston University are turning to young social media users to help build a machine learning program that can spot unwanted sexual advances on Instagram. Trained on data from more than 5 million direct messages — annotated and contributed by 150 adolescents who had experienced conversations that made them feel sexually uncomfortable or unsafe — the technology can quickly and accurately flag risky direct messages (DMs).
The project, which was recently published by the Association for Computing Machinery in its , is intended to address concerns that an increase of teens using social media, particularly during the pandemic, is contributing to .
“In the year 2020 alone, the National Center for Missing and Exploited Children received more than 21.7 million reports of child sexual exploitation — which was a 97% increase over the year prior. This is a very real and terrifying problem,” said Afsaneh Razi, PhD, an assistant professor in Drexel CCI, who was a leader of the research.
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