Phonetic Detection for Hate Speech Spreaders on Twitter
Nowadays, hate messages have become the object of study on social media. Efficient and effective detection of hate profiles requires various scientific disciplines, such as computational linguistics and sociology. Here, we illustrate how we used lexical and phonetic features to determine if the auth...
- Autores:
-
Puertas, Edwin
Martínez-Santos, Juan Carlos
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/10419
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/10419
http://ceur-ws.org/Vol-2936/paper-188.pdf
- Palabra clave:
- Phonetic syllable
Phonetic feature
Feature extraction
Hate speech spreader
LEMB
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
| Summary: | Nowadays, hate messages have become the object of study on social media. Efficient and effective detection of hate profiles requires various scientific disciplines, such as computational linguistics and sociology. Here, we illustrate how we used lexical and phonetic features to determine if the author spreads hate speech. This article presents a novel strategy for the characterization of the Twitter profile based on the generation of lexical and phonetic user features that serve as input to a set of classifiers. The results are part of our participation in the PAN 2021 in the CLEF in the task of Profiling Hate Speech Spreaders on Twitter. |
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