loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Hossam Faris 1 ; Ibrahim Aljarah 1 ; Maria Habib 1 and Pedro A. Castillo 2

Affiliations: 1 Department of Information Technology, King Abdullah II School for Information Technology, The University of Jordan, Amman, Jordan ; 2 Department of Computer Architecture and Technology, ETSIIT - CITIC, University of Granada, Spain

Keyword(s): Hate Speech, Classification, Word Embedding, Machine Learning.

Abstract: Hate speech over online social networks is a worldwide problem that leads for diminishing the cohesion of civil societies. The rapid spread of social media websites is accompanied with an increasing number of social media users which showed a higher rate of hate speech, as well. The objective of this paper is to propose a smart deep learning approach for the automatic detection of cyber hate speech. Particularly, the detection of hate speech on Twitter on the Arabic region. Hence, a dataset is collected from Twitter that captures the hate expressions in different topics at the Arabic region. A set of features extracted from the dataset based on a word embedding mechanism. The word embeddings fed into a deep learning framework. The implemented deep learning approach is a hybrid of convolutional neural network (CNN) and long short-term memory (LSTM) network. The proposed approach achieved good results in classifying tweets as Hate or Normal regarding accuracy, precision, recall, and F1 measure. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.217.237.169

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Faris, H.; Aljarah, I.; Habib, M. and Castillo, P. (2020). Hate Speech Detection using Word Embedding and Deep Learning in the Arabic Language Context. In Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-397-1; ISSN 2184-4313, SciTePress, pages 453-460. DOI: 10.5220/0008954004530460

@conference{icpram20,
author={Hossam Faris. and Ibrahim Aljarah. and Maria Habib. and Pedro A. Castillo.},
title={Hate Speech Detection using Word Embedding and Deep Learning in the Arabic Language Context},
booktitle={Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2020},
pages={453-460},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008954004530460},
isbn={978-989-758-397-1},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Hate Speech Detection using Word Embedding and Deep Learning in the Arabic Language Context
SN - 978-989-758-397-1
IS - 2184-4313
AU - Faris, H.
AU - Aljarah, I.
AU - Habib, M.
AU - Castillo, P.
PY - 2020
SP - 453
EP - 460
DO - 10.5220/0008954004530460
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic