{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T17:09:50Z","timestamp":1780074590923,"version":"3.54.0"},"reference-count":16,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,4,15]],"date-time":"2021-04-15T00:00:00Z","timestamp":1618444800000},"content-version":"vor","delay-in-days":104,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>Pervasive usage and the development of social media networks have provided the platform for the fake news to spread fast among people. Fake news often misleads people and creates wrong society perceptions. The spread of low\u2010quality news in social media has negatively affected individuals and society. In this study, we proposed an ensemble\u2010based deep learning model to classify news as fake or real using LIAR dataset. Due to the nature of the dataset attributes, two deep learning models were used. For the textual attribute \u201cstatement,\u201d Bi\u2010LSTM\u2010GRU\u2010dense deep learning model was used, while for the remaining attributes, dense deep learning model was used. Experimental results showed that the proposed study achieved an accuracy of 0.898, recall of 0.916, precision of 0.913, and <jats:italic>F<\/jats:italic>\u2010score of 0.914, respectively, using only statement attribute. Moreover, the outcome of the proposed models is remarkable when compared with that of the previous studies for fake news detection using LIAR dataset.<\/jats:p>","DOI":"10.1155\/2021\/5557784","type":"journal-article","created":{"date-parts":[[2021,4,15]],"date-time":"2021-04-15T22:50:52Z","timestamp":1618527052000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":121,"title":["Fake Detect: A Deep Learning Ensemble Model for Fake News Detection"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1619-5733","authenticated-orcid":false,"given":"Nida","family":"Aslam","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irfan","family":"Ullah Khan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8949-4550","authenticated-orcid":false,"given":"Farah Salem","family":"Alotaibi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5620-5481","authenticated-orcid":false,"given":"Lama Abdulaziz","family":"Aldaej","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8826-2093","authenticated-orcid":false,"given":"Asma Khaled","family":"Aldubaikil","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,4,15]]},"reference":[{"key":"e_1_2_10_1_2","unstructured":"2021 https:\/\/datareportal.com\/social-media-users Global Social Media Overview."},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1257\/jep.31.2.211"},{"key":"e_1_2_10_3_2","doi-asserted-by":"crossref","unstructured":"Sherry GirgisM. 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