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2020 | OriginalPaper | Chapter

A Dataset to Support Sexist Content Detection in Arabic Text

Authors : Oumayma El Ansari, Zahir Jihad, Mousannif Hajar

Published in: Image and Signal Processing

Publisher: Springer International Publishing

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Abstract

Social media have become a viral source of information. This huge amount of data offers an opportunity to study the feelings and opinions of the crowds toward any subject using Sentiment Analysis, which is a struggling area for Arabic Language. In this research, we present our approach to build a thematic training set by combining manual and automatic annotation of Arabic texts addressing Discrimination and Violence Against Women.

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Taboada, M.: Sentiment analysis: an overview from linguistics. Ann. Rev. Linguist. 2, 325–347 (2016)CrossRef
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Zahir, J.: Mining the web for insights on violence against women in the MENA region and Arab states (2019)
Metadata
Title
A Dataset to Support Sexist Content Detection in Arabic Text
Authors
Oumayma El Ansari
Zahir Jihad
Mousannif Hajar
Copyright Year
2020
Book
Image and Signal Processing

Print ISBN: 978-3-030-51934-6

Electronic ISBN: 978-3-030-51935-3

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-51935-3_14

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