Examining a hate speech corpus for hate speech detection and popularity prediction

Authors

Filip Klubicka, Technological University DublinFollow
Raquel Fernandez, University of AmsterdamFollow

Document Type

Other

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Computer Sciences, Information Science, Linguistics

Publication Details

Published in Proceedings of 4REAL: Workshop on Replicability and Reproducibility of Research Results in Science and Technology of Language

http://4real2018.di.fc.ul.pt/wp-content/uploads/2018/05/lrec2018_workshop_proceedings_4REAL.pdf

Abstract

As research on hate speech becomes more and more relevant every day, most of it is still focused on hate speech detection. By attempting to replicate a hate speech detection experiment performed on an existing Twitter corpus annotated for hate speech, we highlight some issues that arise from doing research in the field of hate speech, which is essentially still in its infancy. We take a critical look at the training corpus in order to understand its biases, while also using it to venture beyond hate speech detection and investigate whether it can be used to shed light on other facets of research, such as popularity of hate tweets.

Recommended Citation

Klublicka, F. & Fernandez, R. Examining a hate speech corpus for hate speech detection and popularity prediction. Proceedings of 4REAL Workshop 9-16 (2018)12 May 2018, Miyazaki, Japan

Funder

SFI