Data set for automatic detection of online misogynistic speech

Theo Lynn; Patricia Takako Endo; Pierangelo Rosati; Ivanovitch Silva; Guto Leoni Santos; Debbie Ging

Data in Brief (Oct 2019)

Data set for automatic detection of online misogynistic speech

Theo Lynn,
Patricia Takako Endo,
Pierangelo Rosati,
Ivanovitch Silva,
Guto Leoni Santos,
Debbie Ging

Affiliations

Theo Lynn: Dublin City University (DCU), Irish Institute of Digital Business (dotLAB), Brazil
Patricia Takako Endo: Corresponding author.; Dublin City University (DCU), Irish Institute of Digital Business (dotLAB), Brazil
Pierangelo Rosati: Dublin City University (DCU), Irish Institute of Digital Business (dotLAB), Brazil
Ivanovitch Silva: Dublin City University (DCU), Irish Institute of Digital Business (dotLAB), Brazil
Guto Leoni Santos: Dublin City University (DCU), Irish Institute of Digital Business (dotLAB), Brazil
Debbie Ging: Dublin City University (DCU), Irish Institute of Digital Business (dotLAB), Brazil

Journal volume & issue: Vol. 26

Abstract

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The data set is composed of 2285 definitions posted on the Urban Dictionary platform from 1999 to May 2016. The data was classified as misogynistic and non-misogynistic by three independent researchers with domain knowledge. The data set is available in public repository in a table containing two columns: the text-based definition from Urban Dictionary and its respective classification (1 for misogynistic and 0 for non-misogynistic). Keywords: Misogyny detection, Misogynistic speech, Hate speech, Online speech, Urban dictionary

Published in Data in Brief

ISSN: 2352-3409 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Science: Science (General)
Website: http://www.journals.elsevier.com/data-in-brief/

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