{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,30]],"date-time":"2025-11-30T09:17:36Z","timestamp":1764494256232,"version":"3.37.3"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3278323","type":"journal-article","created":{"date-parts":[[2023,5,22]],"date-time":"2023-05-22T17:56:07Z","timestamp":1684778167000},"page":"54526-54543","source":"Crossref","is-referenced-by-count":11,"title":["Robust Semi-Supervised Fake News Recognition by Effective Augmentations and Ensemble of Diverse Deep Learners"],"prefix":"10.1109","volume":"11","author":[{"given":"Abdulhameed Al","family":"Obaid","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, RIV Laboratory, Bu-Ali Sina University, Hamedan, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7351-9397","authenticated-orcid":false,"given":"Hassan","family":"Khotanlou","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, RIV Laboratory, Bu-Ali Sina University, Hamedan, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7131-1047","authenticated-orcid":false,"given":"Muharram","family":"Mansoorizadeh","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, RIV Laboratory, Bu-Ali Sina University, Hamedan, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2487-7950","authenticated-orcid":false,"given":"Davood","family":"Zabihzadeh","sequence":"additional","affiliation":[{"name":"Computer Engineering Department, Hakim Sabzevari University, Sabzevar, Iran"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/8885861"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/3434458"},{"key":"ref15","first-page":"596","article-title":"FixMatch: Simplifying semi-supervised learning with consistency and confidence","volume":"33","author":"sohn","year":"2020","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01277"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.03.037"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.12.037"},{"key":"ref17","article-title":"AdaMatch: A unified approach to semi-supervised learning and domain adaptation","author":"berthelot","year":"2021","journal-title":"arXiv 2106 04732"},{"key":"ref16","article-title":"ReMixMatch: Semi-supervised learning with distribution alignment and augmentation anchoring","volume":"abs 1911","author":"berthelot","year":"2019","journal-title":"CoRR"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00934"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01402"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1162\/089976698300017197"},{"key":"ref46","first-page":"1","article-title":"Attention is all you need","volume":"30","author":"vaswani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref45","first-page":"18408","article-title":"FlexMatch: Boosting semi-supervised learning with curriculum pseudo labeling","volume":"34","author":"zhang","year":"2021","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2858821"},{"key":"ref47","article-title":"Explaining and harnessing adversarial examples","author":"goodfellow","year":"2014","journal-title":"arXiv 1412 6572"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107393"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115002"},{"key":"ref44","first-page":"1","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume":"30","author":"tarvainen","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref43","article-title":"Label noise-resistant mean teaching for weakly supervised fake news detection","author":"xie","year":"2022","journal-title":"arXiv 2206 12260"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1089\/big.2020.0062"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113584"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/s42452-020-2326-y"},{"key":"ref9","first-page":"9","article-title":"A deep ensemble framework for fake news detection and multi-class classification of short political statements","author":"roy","year":"2019","journal-title":"Proc 16th Int Conf Natural Lang Process"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.3390\/e24091242"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3395046"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/5557784"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.11.022"},{"key":"ref40","article-title":"Temporal ensembling for semi-supervised learning","author":"laine","year":"2016","journal-title":"arXiv 1610 02242"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1174"},{"key":"ref34","article-title":"Ensemble deep learning: A review","author":"ganaie","year":"2021","journal-title":"arXiv 2104 02395"},{"key":"ref37","article-title":"RoBERTa: A robustly optimized BERT pretraining approach","author":"liu","year":"2019","journal-title":"arXiv 1907 11692"},{"key":"ref36","first-page":"1","article-title":"XLNet: Generalized autoregressive pretraining for language understanding","volume":"32","author":"yang","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219903"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i10.7230"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-2067"},{"key":"ref32","article-title":"TI-CNN: Convolutional neural networks for fake news detection","author":"yang","year":"2018","journal-title":"arXiv 1806 00749"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2019.00062"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3137597.3137600"},{"key":"ref39","article-title":"Deep two-path semi-supervised learning for fake news detection","author":"dong","year":"2019","journal-title":"arXiv 1906 05659"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ASONAM.2018.8508241"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132877"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2019.2899143"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1347"},{"key":"ref25","first-page":"3371","article-title":"Attending sentences to detect satirical fake news","author":"de sarkar","year":"2018","journal-title":"Proc 27th Int Conf Comput Linguistics"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963500"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-13734-6_16"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2013.61"},{"key":"ref28","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2018","journal-title":"arXiv 1810 04805"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-10183-2"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10130161.pdf?arnumber=10130161","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,9]],"date-time":"2023-06-09T14:26:42Z","timestamp":1686320802000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10130161\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":50,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3278323","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2023]]}}}