@inproceedings{solla-etal-2024-sahara,
title = "{S}ahara Pioneers at {FIGNEWS} 2024 Shared Task: Data Annotation Guidelines for Propaganda Detection in News Items",
author = "Solla, Marwa and
Ebrahem, Hassan and
Issa, Alya and
Harmain, Harmain and
Nwesri, Abdusalam",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha, Ibrahim and
Abdelali, Ahmed and
Touileb, Samia and
Hamed, Injy and
Onaizan, Yaser and
Alhafni, Bashar and
Antoun, Wissam and
Khalifa, Salam and
Haddad, Hatem and
Zitouni, Imed and
AlKhamissi, Badr and
Almatham, Rawan and
Mrini, Khalil",
booktitle = "Proceedings of The Second Arabic Natural Language Processing Conference",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.arabicnlp-1.64",
pages = "601--608",
abstract = "In today{'}s digital age, the spread of propaganda through news channels has become a pressing concern. To address this issue, the research community has organized a shared task on detecting propaganda in news posts. This paper aims to present the work carried out at the University of Tripoli for the development and implementation of data annotation guidelines by a team of five annotators. The guidelines were used to annotate 2600 news articles. Each article is labeled as {``}propaganda{''}, {``}Not propaganda{''}, {``}Not Applicable{''}, or {``}Not clear{''}. The shared task results put our efforts in the third position among 6 participating teams in the consistency track.",
}
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<abstract>In today’s digital age, the spread of propaganda through news channels has become a pressing concern. To address this issue, the research community has organized a shared task on detecting propaganda in news posts. This paper aims to present the work carried out at the University of Tripoli for the development and implementation of data annotation guidelines by a team of five annotators. The guidelines were used to annotate 2600 news articles. Each article is labeled as “propaganda”, “Not propaganda”, “Not Applicable”, or “Not clear”. The shared task results put our efforts in the third position among 6 participating teams in the consistency track.</abstract>
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%0 Conference Proceedings
%T Sahara Pioneers at FIGNEWS 2024 Shared Task: Data Annotation Guidelines for Propaganda Detection in News Items
%A Solla, Marwa
%A Ebrahem, Hassan
%A Issa, Alya
%A Harmain, Harmain
%A Nwesri, Abdusalam
%Y Habash, Nizar
%Y Bouamor, Houda
%Y Eskander, Ramy
%Y Tomeh, Nadi
%Y Abu Farha, Ibrahim
%Y Abdelali, Ahmed
%Y Touileb, Samia
%Y Hamed, Injy
%Y Onaizan, Yaser
%Y Alhafni, Bashar
%Y Antoun, Wissam
%Y Khalifa, Salam
%Y Haddad, Hatem
%Y Zitouni, Imed
%Y AlKhamissi, Badr
%Y Almatham, Rawan
%Y Mrini, Khalil
%S Proceedings of The Second Arabic Natural Language Processing Conference
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F solla-etal-2024-sahara
%X In today’s digital age, the spread of propaganda through news channels has become a pressing concern. To address this issue, the research community has organized a shared task on detecting propaganda in news posts. This paper aims to present the work carried out at the University of Tripoli for the development and implementation of data annotation guidelines by a team of five annotators. The guidelines were used to annotate 2600 news articles. Each article is labeled as “propaganda”, “Not propaganda”, “Not Applicable”, or “Not clear”. The shared task results put our efforts in the third position among 6 participating teams in the consistency track.
%U https://aclanthology.org/2024.arabicnlp-1.64
%P 601-608
Markdown (Informal)
[Sahara Pioneers at FIGNEWS 2024 Shared Task: Data Annotation Guidelines for Propaganda Detection in News Items](https://aclanthology.org/2024.arabicnlp-1.64) (Solla et al., ArabicNLP-WS 2024)
ACL