{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T13:46:23Z","timestamp":1778852783774,"version":"3.51.4"},"reference-count":52,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,5,13]],"date-time":"2022-05-13T00:00:00Z","timestamp":1652400000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>The fast growth of technology in online communication and social media platforms alleviated numerous difficulties during the COVID-19 epidemic. However, it was utilized to propagate falsehoods and misleading information about the disease and the vaccination. In this study, we investigate the ability of deep neural networks, namely, Long Short-Term Memory (LSTM), Bi-directional LSTM, Convolutional Neural Network (CNN), and a hybrid of CNN and LSTM networks, to automatically classify and identify fake news content related to the COVID-19 pandemic posted on social media platforms. These deep neural networks have been trained and tested using the \u201cCOVID-19 Fake News\u201d dataset, which contains 21,379 real and fake news instances for the COVID-19 pandemic and its vaccines. The real news data were collected from independent and internationally reliable institutions on the web, such as the World Health Organization (WHO), the International Committee of the Red Cross (ICRC), the United Nations (UN), the United Nations Children\u2019s Fund (UNICEF), and their official accounts on Twitter. The fake news data were collected from different fact-checking websites (such as Snopes, PolitiFact, and FactCheck). The evaluation results showed that the CNN model outperforms the other deep neural networks with the best accuracy of 94.2%.<\/jats:p>","DOI":"10.3390\/data7050065","type":"journal-article","created":{"date-parts":[[2022,5,13]],"date-time":"2022-05-13T08:37:02Z","timestamp":1652431022000},"page":"65","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":53,"title":["A Deep Learning Framework for Detection of COVID-19 Fake News on Social Media Platforms"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4248-8732","authenticated-orcid":false,"given":"Yahya","family":"Tashtoush","sequence":"first","affiliation":[{"name":"Computer Science Department, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Balqis","family":"Alrababah","sequence":"additional","affiliation":[{"name":"Computer Science Department, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8346-7148","authenticated-orcid":false,"given":"Omar","family":"Darwish","sequence":"additional","affiliation":[{"name":"Information Security and Applied Computing Department, Eastern Michigan University, Ypsilanti, MI 48197, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Majdi","family":"Maabreh","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Faculty of Prince Al-Hussein Bin Abdallah II For Information Technology, The Hashemite University, P.O. Box 330127, Zarqa 13133, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nasser","family":"Alsaedi","sequence":"additional","affiliation":[{"name":"Computer Science Department, Taibah University, Medina 2003, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Al-Ahmad, B., Al-Zoubi, A.M., Abu Khurma, R., and Aljarah, I. (2021). An Evolutionary Fake News Detection Method for COVID-19 Pandemic Information. Symmetry, 13.","DOI":"10.3390\/sym13061091"},{"key":"ref_2","unstructured":"(2021, December 20). COVID-19 Pandemic\u2014Wikipedia. Available online: https:\/\/en.wikipedia.org\/wiki\/COVID-19_pandemic."},{"key":"ref_3","unstructured":"(2022, April 15). Coronavirus: Hundreds Dead in Iran from Drinking Methanol Amid Fake Reports It Cures Disease. 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