license: apache-2.0
language:
- es
Dataset Card for OffendES
Table of Contents
Dataset Description
- Paper: OffendES: A New Corpus in Spanish for Offensive Language Research
- Leaderboard: Leaderboard for OffendES / Spanish
- Point of Contact: [email protected]
Dataset Summary
Focusing on young influencers from the well-known social platforms of Twitter, Instagram, and YouTube, we have collected a corpus composed of Spanish comments manually labeled on offensive pre-defined categories. From the total corpus, we selected 30,416 posts to be publicly published, they correspond to the ones used in the MeOffendES competition at IberLEF 2021. The posts are labeled with the following categories:
- Offensive, the target is a person (OFP). Offensive text targeting a specific individual.
- Offensive, the target is a group of people or collective (OFG). Offensive text targeting a group of people belonging to the same ethnic group, gender or sexual orientation, political ideology, religious belief, or other common characteristics.
- Non-offensive, but with expletive language (NOE). A text that contains rude words, blasphemes, or swearwords but without the aim of offending, and usually with a positive connotation.
- Non-offensive (NO). Text that is neither offensive nor contains expletive language
Supported Tasks and Leaderboards
This dataset is intended for multi-class offensive classification and binary offensive classification. Competition MeOffendES task on offensive detection for Spanish at IberLEF 2021
Languages
- Spanish
Dataset Structure
Data Instances
For each instance, there is a string for the id of the tweet, a string for the emotion class, a string for the offensive class, and a string for the event. See the to explore more examples.
{'comment_id': '8003',
'influencer': 'dalas',
'comment': 'Estupido aburrido',
'label': 'NO',
'influencer_gender': 'man',
'media': youtube
}
Data Fields
comment_id: a string to identify the commentinfluencer: a string containing the influencer associated with the commentcomment: a string containing the text of the commentlabel: a string containing the offensive gold labelinfluencer_gender: a string containing the genre of the influencermedia: a string containing the social media platform where the comment has been retrieved
Data Splits
The OffendES dataset contains 3 splits: train, validation, and test. Below are the statistics for each class.
| OffendES | Number of Instances in Split per class | ||
|---|---|---|---|
Class |
Train |
Validation |
Test |
| NO | 13,212 | 64 | 9,651 |
| NOE | 1,235 | 22 | 2,340 |
| OFP | 2,051 | 10 | 1,404 |
| OFG | 212 | 4 | 211 |
| Total | 16,710 | 100 | 13,606 |
Dataset Creation
Source Data
Twitter, Youtube, Instagram
Who are the annotators?
Amazon Mechanical Turkers
Additional Information
Licensing Information
The OffendES dataset is released under the Apache-2.0 License.
Citation Information
@inproceedings{plaza-del-arco-etal-2021-offendes,
title = "{O}ffend{ES}: A New Corpus in {S}panish for Offensive Language Research",
author = "{Plaza-del-Arco}, Flor Miriam and Montejo-R{\'a}ez, Arturo and Ure{\~n}a-L{\'o}pez, L. Alfonso and Mart{\'\i}n-Valdivia, Mar{\'\i}a-Teresa",
booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
month = sep,
year = "2021",
address = "Held Online",
url = "https://aclanthology.org/2021.ranlp-1.123.pdf",
language = "English",
pages = "1096--1108"
}
@article{meoffendes2021,
title="{{Overview of MeOffendEs at IberLEF 2021: Offensive Language Detection in Spanish Variants}}",
author="{Flor Miriam Plaza-del-Arco and Casavantes, Marco and Jair Escalante, Hugo and Martín-Valdivia, M. Teresa and Montejo-Ráez, Arturo and {Montes-y-Gómez}, Manuel and Jarquín-Vásquez, Horacio and Villaseñor-Pineda, Luis}",
journal="Procesamiento del Lenguaje Natural",
url = "https://bit.ly/3QpRDfy",
volume="67",
pages="183--194",
year="2021"
}