Classification of comments into different categories with contextual information. No information about the comment (source or influencer ID) is provided.
The following categories are considered:
- Offensive, target is a person (OFP). Offensive text targeting a specific individual.
- Offensive, 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 characteristic.
- Offensive, target is different from a person or a group (OFO). Offensive text where the target does not belong to any of the previous categories, e.g., an organization, an event, a place, an issue.
- 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.
Publication
Flor Miriam Plaza-del-Arco, Marco Casavantes, Hugo Jair Escalante, M. Teresa Martín-Valdivia, Arturo Montejo-Ráez, Manuel Montes-y-Gómez, Horacio Jarquín-Vásquez, Luis Villaseñor-Pineda (2021) Overview of MeOffendEs at IberLEF 2021: Offensive Language Detection in Spanish Variants.Procesamiento del Lenguaje Natural, Revista nº 67, septiembre de 2021, pp. 183-194.
Competition
Language
Spanish
NLP topic
Abstract task
Dataset
Year
2021
Publication link
Ranking metric
Micro F
Task results
System | MicroPrecision | MicroRecall | MicroF1 Sort ascending |
---|---|---|---|
NLP-CIC | 0.7679 | 0.7093 | 0.7324 |
UMUTeam | 0.7861 | 0.6919 | 0.7301 |
GDUFS DM | 0.7565 | 0.7002 | 0.7239 |
Marta Isabel | 0.5781 | 0.5451 | 0.5595 |