Agenda

Hate-speech detection is not as easy as it seems: A tale of bias, overfitting and experimental errors
04/jun

ABSTRACT

Hate speech is an important problem that is seriously affecting the dynamics and usefulness of online social communities. Large scale social platforms are currently investing important resources into automatically detecting and classifying hateful content, without much success. On the other hand, the results reported by state-of-the-art systems indicate that supervised approaches achieve almost perfect performance but only within specific datasets. This talk explores this apparent contradiction between existing literature and actual applications and presents evidence of methodological issues, as well as an important dataset bias.

 

PRESENTER

Barbara Poblete, PhD – Associate Professor – University of Chile

 

WHEN AND WHERE

June 4th, at 14.00 hrs (EST Time, Santiago)

Registration: https://ncsu.zoom.us/meeting/register/tJYudeqprDkvHtaYgKt9GUCON1S-rhemUHeI

More info: https://responsibleml.iaa.ncsu.edu