{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T18:55:25Z","timestamp":1782586525248,"version":"3.54.5"},"reference-count":28,"publisher":"Walter de Gruyter GmbH","issue":"2","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>In an era characterised by the rapid dissemination of information through digital platforms, the proliferation of fake news has emerged as a pressing global concern. Misinformation, deliberately fabricated or misleading content presented as factual news, poses significant threats to public discourse, trust, and decision-making processes. The research highlights the significance of fake news detection in the Arabic language, with a specific focus on the Algerian dialect. The Arabic language exhibits great diversity and complexity, making the detection of false information, all the more crucial. The rapid spread of fake news through social media platforms has a significant impact on individuals and society as a whole. To address this challenge, this paper presents TruthGuardian, an innovative solution that combines machine learning and deep learning techniques with voting system for the last decision. This solution enables fast and accurate identification of fake news in the Arabic language, with emphasis on the Algerian dialect. It provides reliable and effective results in countering misinformation.<\/jats:p>","DOI":"10.2478\/acss-2024-0017","type":"journal-article","created":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T13:12:44Z","timestamp":1733490764000},"page":"14-21","source":"Crossref","is-referenced-by-count":4,"title":["Detection of Arabic and Algerian Fake News"],"prefix":"10.2478","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0873-6384","authenticated-orcid":false,"given":"Khaoula","family":"Hamadouche","sequence":"first","affiliation":[{"name":"Computer Science Department , University of Oran 1 , Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8252-3291","authenticated-orcid":false,"given":"Kheira Zineb","family":"Bousmaha","sequence":"additional","affiliation":[{"name":"Computer Science Department , University of Oran 1 , Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-5246-183X","authenticated-orcid":false,"given":"Mohamed Yasine Bahi","family":"Amar","sequence":"additional","affiliation":[{"name":"Computer Science Department , University of Oran 1 , Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4868-657X","authenticated-orcid":false,"given":"Lamia","family":"Hadrich-Belguith","sequence":"additional","affiliation":[{"name":"Computer Science Department , MIRACL laboratory, FSEGS, University of Sfax , Tunisia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2024,12,6]]},"reference":[{"key":"2026060415415057712_j_acss-2024-0017_ref_001","doi-asserted-by":"crossref","unstructured":"S. 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