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2024 | OriginalPaper | Chapter

Annotating Social Data with Speaker/User Engagement. Illustration on Online Hate Characterization in French

Authors : Delphine Battistelli, Valentina Dragos, Jade Mekki

Published in: Proceedings of Third International Conference on Computing and Communication Networks

Publisher: Springer Nature Singapore

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Abstract

This paper presents an annotation framework relying on the linguistic notion of speaker/user engagement. This notion is suitable for a finer characteriza- tion of online hateful discourse as it allows addressing the following question: does the speaker engage himself to the truthfulness of hate content? Two resources were built to support the annotation framework: a taxonomy of speaker/user engage- ment degrees and a rich semantic resource of pictograms/emoticons. The paper describes the resources used and the annotation process. Preliminary experiments and results on sexism characterization in French are also presented.

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Footnotes
2
The definition of sexism used it’s the one given by the European Council.
 
3
Supervised learning models from scikit-learn.
 
4
Ktrain’s GitHub.
 
5
CamemBERT-base version on Hugging Face site.
 
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Metadata
Title
Annotating Social Data with Speaker/User Engagement. Illustration on Online Hate Characterization in French
Authors
Delphine Battistelli
Valentina Dragos
Jade Mekki
Copyright Year
2024
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-97-0892-5_25