News
Monday, November 5, 2012
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
