@inproceedings{fersini-etal-2020-profiling,
title = "Profiling {I}talian Misogynist: An Empirical Study",
author = "Fersini, Elisabetta and
Nozza, Debora and
Boifava, Giulia",
editor = "Monti, Johanna and
Basile, Valerio and
Buono, Maria Pia Di and
Manna, Raffaele and
Pascucci, Antonio and
Tonelli, Sara",
booktitle = "Proceedings of the Workshop on Resources and Techniques for User and Author Profiling in Abusive Language",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/2020.restup-1.3",
pages = "9--13",
abstract = "Hate speech may take different forms in online social environments. In this paper, we address the problem of automatic detection of misogynous language on Italian tweets by focusing both on raw text and stylometric profiles. The proposed exploratory investigation about the adoption of stylometry for enhancing the recognition capabilities of machine learning models has demonstrated that profiling users can lead to good discrimination of misogynous and not misogynous contents.",
language = "English",
ISBN = "979-10-95546-49-8",
}
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<abstract>Hate speech may take different forms in online social environments. In this paper, we address the problem of automatic detection of misogynous language on Italian tweets by focusing both on raw text and stylometric profiles. The proposed exploratory investigation about the adoption of stylometry for enhancing the recognition capabilities of machine learning models has demonstrated that profiling users can lead to good discrimination of misogynous and not misogynous contents.</abstract>
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%0 Conference Proceedings
%T Profiling Italian Misogynist: An Empirical Study
%A Fersini, Elisabetta
%A Nozza, Debora
%A Boifava, Giulia
%Y Monti, Johanna
%Y Basile, Valerio
%Y Buono, Maria Pia Di
%Y Manna, Raffaele
%Y Pascucci, Antonio
%Y Tonelli, Sara
%S Proceedings of the Workshop on Resources and Techniques for User and Author Profiling in Abusive Language
%D 2020
%8 May
%I European Language Resources Association (ELRA)
%C Marseille, France
%@ 979-10-95546-49-8
%G English
%F fersini-etal-2020-profiling
%X Hate speech may take different forms in online social environments. In this paper, we address the problem of automatic detection of misogynous language on Italian tweets by focusing both on raw text and stylometric profiles. The proposed exploratory investigation about the adoption of stylometry for enhancing the recognition capabilities of machine learning models has demonstrated that profiling users can lead to good discrimination of misogynous and not misogynous contents.
%U https://aclanthology.org/2020.restup-1.3
%P 9-13
Markdown (Informal)
[Profiling Italian Misogynist: An Empirical Study](https://aclanthology.org/2020.restup-1.3) (Fersini et al., ResTUP 2020)
ACL
- Elisabetta Fersini, Debora Nozza, and Giulia Boifava. 2020. Profiling Italian Misogynist: An Empirical Study. In Proceedings of the Workshop on Resources and Techniques for User and Author Profiling in Abusive Language, pages 9–13, Marseille, France. European Language Resources Association (ELRA).