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metadata
language:
  - es
pretty_name: contextualized_hate_speech
task_categories:
  - text-classification
tags:
  - hate_speech
size_categories:
  - 10K<n<100K

Contextualized Hate Speech: A dataset of comments in news outlets on Twitter

Dataset Description

Dataset Summary

Graphical representation of the dataset This dataset is a collection of tweets posted in response to news articles from five specific Argentinean news outlets: Clarín, Infobae, La Nación, Perfil and Crónica, during the COVID-19 pandemic. The comments were annotated for the presence of hate speech across eight different characteristics: against women, racist content, class hatred, against LGBTQ+ individuals, against physical appearance, against people with disabilities, against criminals, and for political reasons. All the data is in Spanish.

Each comment is labeled with the following variables

Label Description
HATEFUL Contains hate speech (HS)?
CALLS If it is hateful, is this message calling to (possibly violent) action?
WOMEN Is this against women?
LGBTI Is this against LGBTI people?
RACISM Is this a racist message?
CLASS Is this a classist message?
POLITICS Is this HS due to political ideology?
DISABLED Is this HS against disabled people?
APPEARANCE Is this HS against people due to their appearance? (e.g. fatshaming)
CRIMINAL Is this HS against criminals or people in conflict with law?

There is an extra label CALLS, which represents whether a comment is a call to violent action or not.

For each comment, we have a list of annotators who marked the comment first as HATEFUL, and then the selected categories (one or more).

An aggregated version of the dataset can be found at piuba-bigdata/contextualized_hate_speech

Citation Information

@article{perez2022contextual,
  author  = {Pérez, Juan Manuel and Luque, Franco M. and Zayat, Demian and Kondratzky, Martín and Moro, Agustín and Serrati, Pablo Santiago and Zajac, Joaquín and Miguel, Paula and Debandi, Natalia and Gravano, Agustín and Cotik, Viviana},
  journal = {IEEE Access},
  title   = {Assessing the Impact of Contextual Information in Hate Speech Detection},
  year    = {2023},
  volume  = {11},
  number  = {},
  pages   = {30575-30590},
  doi     = {10.1109/ACCESS.2023.3258973}
}

Contributions

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