Simply by looking at these different rates of word usage, Schnoebelen and his colleagues, David Bamman of Carnegie Mellon University and Jacob Eisenstein (Interactive Comp) of Georgia Tech, can predict the gender of an author on Twitter with 88 percent accuracy. Source: The Boston Globe
- Groups
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College of Computing, School of Interactive Computing
- Categories
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Computer Science/Information Technology and Security, Digital Media and Entertainment
- Keywords
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Jacob Eisenstein; gender; Twitter; social media; language; linguistics
- Status
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- Created By: Michaelanne Dye
- Workflow Status: Published
- Created On: Nov 6, 2012 - 10:19am
- Last Updated: Oct 7, 2016 - 10:26pm