Analyzing gender-based violence and aggressive behavior through social media data

Sneha Revanur, California, USA 13-15

“I had a PhD, multiple awards, many friends, and a life that appeared to many to be quite lovely. And yet he hit me,” read one of the posts I collected through a computational model I developed that recognizes relevance to gender-based violence in tweets. Gender-based violence encompasses globally prevalent issues like domestic violence, child marriage, human trafficking, and maternal health; hundreds of millions of people lay victim to GBV. With my model, I leverage natural language processing and machine learning to uncover how social media can inform our efforts to combat one of our world's largest humanitarian crises.

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