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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Hugo Rosa, João P. Carvalho, Pável Calado, Bruno Martins, Ribeiro, R. & L. Coheur (2018). Using Fuzzy Fingerprints for Cyberbullying Detection in Social Networks. 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).
Exportar Referência (IEEE) 
H. Rosa et al.,  "Using Fuzzy Fingerprints for Cyberbullying Detection in Social Networks", in 2018 IEEE Int. Conf. on Fuzzy Systems (FUZZ-IEEE), Rio de Janeiro, 2018
Exportar BibTeX 
@misc{rosa2018_1736945499365,
	author = "Hugo Rosa and João P. Carvalho and Pável Calado and Bruno Martins and Ribeiro, R. and L. Coheur",
	title = "Using Fuzzy Fingerprints for Cyberbullying Detection in Social Networks",
	year = "2018",
	howpublished = "Digital"
}
Exportar RIS 
TY  - CPAPER
TI  - Using Fuzzy Fingerprints for Cyberbullying Detection in Social Networks
T2  - 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
AU  - Hugo Rosa
AU  - João P. Carvalho
AU  - Pável Calado
AU  - Bruno Martins
AU  - Ribeiro, R.
AU  - L. Coheur
PY  - 2018
CY  - Rio de Janeiro
AB  - As cyberbullying becomes more and more frequent in social networks, automatically detecting it and pro-actively acting upon it becomes of the utmost importance. In this work, we study how a recent technique with proven success in similar tasks, Fuzzy Fingerprints, performs when detecting textual cyberbullying in social networks. Despite being commonly treated as binary classification task, we argue that this is in fact a retrieval problem where the only relevant performance is that of retrieving cyberbullying interactions. Experiments show that the Fuzzy Fingerprints slightly outperforms baseline classifiers when tested in a close to real life scenario, where cyberbullying instances are rarer than those without cyberbullying.
ER  -