{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T16:41:18Z","timestamp":1784738478994,"version":"3.55.0"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2021,1,7]],"date-time":"2021-01-07T00:00:00Z","timestamp":1609977600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,1,7]],"date-time":"2021-01-07T00:00:00Z","timestamp":1609977600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,3]]},"DOI":"10.1007\/s11042-020-10183-2","type":"journal-article","created":{"date-parts":[[2021,1,7]],"date-time":"2021-01-07T12:03:36Z","timestamp":1610021016000},"page":"11765-11788","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":645,"title":["FakeBERT: Fake news detection in social media with a BERT-based deep learning approach"],"prefix":"10.1007","volume":"80","author":[{"given":"Rohit Kumar","family":"Kaliyar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anurag","family":"Goswami","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1865-3512","authenticated-orcid":false,"given":"Pratik","family":"Narang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,1,7]]},"reference":[{"key":"10183_CR1","doi-asserted-by":"crossref","unstructured":"Ahmed H, Traore I, Saad S (2017) Detection of online fake news using N-gram analysis and machine learning techniques. In: International conference on intelligent, secure, and dependable systems in distributed and cloud environments. Springer, Cham, pp 127\u2013138","DOI":"10.1007\/978-3-319-69155-8_9"},{"issue":"2","key":"10183_CR2","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1257\/jep.31.2.211","volume":"31","author":"H Allcott","year":"2017","unstructured":"Allcott H, Gentzkow M (2017) Social media and fake news in the 2016 election. J Econ Perspect 31(2):211\u201336","journal-title":"J Econ Perspect"},{"key":"10183_CR3","unstructured":"Asparouhov T, Muth\u00e9n B (2010) Weighted least squares estimation with missing data. Mplus Technical Appendix 2010: 1\u201310"},{"key":"10183_CR4","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.ins.2019.05.035","volume":"497","author":"A Bondielli","year":"2019","unstructured":"Bondielli A, Marcelloni F (2019) A survey on fake news and rumour detection techniques. Inform Sci 497:38\u201355","journal-title":"Inform Sci"},{"key":"10183_CR5","doi-asserted-by":"crossref","unstructured":"Castillo C, Mendoza M, Poblete B (2011) Information credibility on twitter. In: Proceedings of the 20th international conference on world wide web, pp 675\u2013684","DOI":"10.1145\/1963405.1963500"},{"key":"10183_CR6","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1016\/j.csl.2017.07.009","volume":"47","author":"C Cerisara","year":"2018","unstructured":"Cerisara C, Kral P, Lenc L (2018) On the effects of using word2vec representations in neural networks for dialogue act recognition. Comput Speech Lang 47:175\u2013193","journal-title":"Comput Speech Lang"},{"key":"10183_CR7","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.patrec.2017.10.014","volume":"105","author":"W Chen","year":"2018","unstructured":"Chen W, Zhang Y, Yeo CK, Lau CT, Sung Lee B (2018) Unsupervised rumor detection based on users\u2019 behaviors using neural networks. Pattern Recogn Lett 105:226\u2013233","journal-title":"Pattern Recogn Lett"},{"key":"10183_CR8","doi-asserted-by":"crossref","unstructured":"Crestani F, Rosso P (2020) The role of personality and linguistic patterns in discriminating between fake news spreaders and fact checkers. In: Natural language processing and information systems: 25th international conference on applications of natural language to information systems, NLDB 2020, Saarbr\u00fccken, Germany. Proceedings, vol 181. Springer Nature","DOI":"10.1007\/978-3-030-51310-8_17"},{"key":"10183_CR9","unstructured":"De S, Sohan FY, Mukherjee A (2018) Attending sentences to detect satirical fake news. In: Proceedings of the 27th international conference on computational linguistics, pp 3371\u20133380"},{"issue":"3","key":"10183_CR10","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1073\/pnas.1517441113","volume":"113","author":"M Del Vicario","year":"2016","unstructured":"Del Vicario M, Bessi A, Zollo F, Petroni F, Scala A, Caldarelli G, Eugene Stanley H, Quattrociocchi W (2016) The spreading of misinformation online. Proceedings of the National Academy of Sciences 113(3):554\u2013559","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"10183_CR11","unstructured":"Devlin J, Chang M-W, Lee K, Kristina T (2019) BERT: Pre-training of deep bidirectional transformers for language understanding. In: NAACL-HLT (1)"},{"issue":"11","key":"10183_CR12","doi-asserted-by":"publisher","first-page":"2707","DOI":"10.1109\/TIFS.2018.2825958","volume":"13","author":"M Fazil","year":"2018","unstructured":"Fazil M, Abulaish M (2018) A hybrid approach for detecting automated spammers in twitter. IEEE Trans Inf Forensics Secur 13(11):2707\u20132719","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"10183_CR13","doi-asserted-by":"crossref","unstructured":"Ghanem B, Rosso P, Rangel F (2018) Stance detection in fake news a combined feature representation. In: Proceedings of the first workshop on fact extraction and VERification (FEVER), pp 66\u201371","DOI":"10.18653\/v1\/W18-5510"},{"issue":"1","key":"10183_CR14","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1002\/pra2.2018.14505501125","volume":"55","author":"S Ghosh","year":"2018","unstructured":"Ghosh S, Shah C (2018) Towards automatic fake news classification. Proc Assoc Inf Sci Technol 55(1):805\u2013807","journal-title":"Proc Assoc Inf Sci Technol"},{"issue":"10","key":"10183_CR15","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.1109\/TNNLS.2016.2582924","volume":"28","author":"K Greff","year":"2016","unstructured":"Greff K, Srivastava RK, Koutn\u00edk J, Steunebrink BR, Schmidhuber J (2016) LSTM: A search space odyssey. IEEE Trans Neural Netw Learn Syst 28(10):2222\u20132232","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"10183_CR16","doi-asserted-by":"crossref","unstructured":"Gorrell G, Kochkina E, Liakata M, Aker A, Zubiaga A, Bontcheva K, Derczynski L (2019) SemEval-2019 task 7: RumourEval, determining rumour veracity and support for rumours. In: Proceedings of the 13th International Workshop on Semantic Evaluation, pp. 845\u2013854","DOI":"10.18653\/v1\/S19-2147"},{"key":"10183_CR17","doi-asserted-by":"crossref","unstructured":"Gupta M, Zhao P, Han J (2012) Evaluating event credibility on twitter. In: Proceedings of the 2012 SIAM international conference on data mining. Society for industrial and applied mathematics, pp 153\u2013164","DOI":"10.1137\/1.9781611972825.14"},{"issue":"19","key":"10183_CR18","doi-asserted-by":"publisher","first-page":"4062","DOI":"10.3390\/app9194062","volume":"9","author":"H Jwa","year":"2019","unstructured":"Jwa H, Oh D, Park K, Kang JM, Lim H (2019) exBAKE: Automatic fake news detection model based on bidirectional encoder representations from transformers (BERT). Appl Sci 9(19):4062","journal-title":"Appl Sci"},{"key":"10183_CR19","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.cogsys.2019.12.005","volume":"61","author":"RK Kaliyar","year":"2020","unstructured":"Kaliyar RK, Goswami A, Narang P, Sinha S (2020) FNDNetA deep convolutional neural network for fake news detection. Cognitive Systems Research 61:32\u201344","journal-title":"Cognitive Systems Research"},{"key":"10183_CR20","unstructured":"Karimi H, Roy P, Saba-Sadiya S, Tang J (2018) Multi-source multi-class fake news detection. In: Proceedings of the 27th international conference on computational linguistics, pp 1546\u20131557"},{"key":"10183_CR21","unstructured":"Kumar S, Shah N (2018) False information on web and social media: a survey. arXiv:arXiv-1804"},{"key":"10183_CR22","unstructured":"Li Y, Yuan Y (2017) Convergence analysis of two-layer neural networks with relu activation"},{"key":"10183_CR23","doi-asserted-by":"crossref","unstructured":"Liu Y, Yi-Fang BW (2018) Early detection of fake news on social media through propagation path classification with recurrent and convolutional networks. In: Thirty-second AAAI conference on artificial intelligence","DOI":"10.1609\/aaai.v32i1.11268"},{"issue":"1","key":"10183_CR24","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1109\/43.62793","volume":"10","author":"S Malik","year":"1991","unstructured":"Malik S, Sentovich EM, Brayton RK, Sangiovanni-Vincentelli A (1991) Retiming and resynthesis: Optimizing sequential networks with combinational techniques. IEEE Trans Comput-Aided Design Integr Circuits Syst 10(1):74\u201384","journal-title":"IEEE Trans Comput-Aided Design Integr Circuits Syst"},{"key":"10183_CR25","doi-asserted-by":"crossref","unstructured":"Monteiro RA, Santos RLS, Pardo TAS, de Almeida TA, Ruiz EES, Vale OA (2018) Contributions to the study of fake news in portuguese: New corpus and automatic detection results. In: International conference on computational processing of the portuguese language. Springer, Cham, pp 324\u2013334","DOI":"10.1007\/978-3-319-99722-3_33"},{"key":"10183_CR26","doi-asserted-by":"crossref","unstructured":"Munandar D, Arisal A, Riswantini D, Rozie AF (2018) Text classification for sentiment prediction of social media dataset using multichannel convolution neural network. In: 2018 International conference on computer, control, informatics and its applications (IC3INA). IEEE, pp 104\u2013109","DOI":"10.1109\/IC3INA.2018.8629522"},{"key":"10183_CR27","doi-asserted-by":"crossref","unstructured":"Nagi J, Ducatelle F, Di Caro GA, Cire\u015fan D, Meier U, Giusti A, Nagi F, Schmidhuber J, Gambardella LM (2011) Max-pooling convolutional neural networks for vision-based hand gesture recognition, IEEE","DOI":"10.1109\/ICSIPA.2011.6144164"},{"key":"10183_CR28","unstructured":"O\u2019Brien N, Latessa S, Evangelopoulos G, Boix X (2018) The language of fake news: Opening the black-box of deep learning based detectors"},{"key":"10183_CR29","unstructured":"P\u00e9rez-Rosas Ver\u00f3nica, Kleinberg B, Lefevre A, Mihalcea R (2018) Automatic detection of fake news. In: Proceedings of the 27th international conference on computational linguistics, pp 3391\u20133401"},{"key":"10183_CR30","doi-asserted-by":"crossref","unstructured":"Peters ME, Neumann M, Iyyer M, Gardner M, Clark C, Lee K, Zettlemoyer L (2018) Deep contextualized word representations. In: Proceedings of NAACL-HLT, pp 2227\u20132237","DOI":"10.18653\/v1\/N18-1202"},{"key":"10183_CR31","doi-asserted-by":"crossref","unstructured":"Qi Y, Sachan D, Felix M, Padmanabhan S, Neubig G (2018) When and why are pre-trained word embeddings useful for neural machine translation?. In: Proceedings of the 2018 conference of the north american chapter of the association for computational linguistics: human language technologies, vol 2 (short papers), pp 529\u2013535","DOI":"10.18653\/v1\/N18-2084"},{"key":"10183_CR32","doi-asserted-by":"crossref","unstructured":"Rashkin H, Choi E, Jang JY, Volkova S, Choi Y (2017) Truth of varying shades: Analyzing language in fake news and political fact-checking. In: Proceedings of the 2017 conference on empirical methods in natural language processing, pp 2931\u20132937","DOI":"10.18653\/v1\/D17-1317"},{"issue":"3","key":"10183_CR33","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1007\/s10796-017-9805-8","volume":"20","author":"A Reema","year":"2018","unstructured":"Reema A, Kar AK, Vigneswara Ilavarasan P (2018) Detection of spammers in twitter marketing: a hybrid approach using social media analytics and bio inspired computing. Information Systems Frontiers 20(3):515\u2013530","journal-title":"Information Systems Frontiers"},{"key":"10183_CR34","unstructured":"Roy A, Basak K, Ekbal A, Bhattacharyya P (2018) A deep ensemble framework for fake news detection and classification. arXiv:arXiv-1811"},{"key":"10183_CR35","doi-asserted-by":"crossref","unstructured":"Ruchansky N, Seo S, Liu Y (2017) Csi: A hybrid deep model for fake news detection. In: Proceedings of the 2017 ACM on conference on information and knowledge management. ACM, pp 797\u2013806","DOI":"10.1145\/3132847.3132877"},{"key":"10183_CR36","doi-asserted-by":"crossref","unstructured":"Seide F, Li G, Chen X, Yu D (2011) Feature engineering in context-dependent deep neural networks for conversational speech transcription, IEEE","DOI":"10.1109\/ASRU.2011.6163899"},{"key":"10183_CR37","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1016\/j.chb.2018.02.008","volume":"8","author":"J Shin","year":"2018","unstructured":"Shin J, Jian L, Driscoll K, Bar F (2018) The diffusion of misinformation on social media: Temporal pattern, message, and source. Comput Hum Behav 8:278\u2013287","journal-title":"Comput Hum Behav"},{"key":"10183_CR38","doi-asserted-by":"crossref","unstructured":"Shu K, Cui L, Wang S, Lee D, Liu H (2019) defend: Explainable fake news detection. In: Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining, pp 395\u2013405","DOI":"10.1145\/3292500.3330935"},{"issue":"3","key":"10183_CR39","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1089\/big.2020.0062","volume":"8","author":"K Shu","year":"2020","unstructured":"Shu K, Mahudeswaran D, Wang S, Lee D, Liu H (2020) FakeNewsNet: A data repository with news content, social context, and spatio temporal information for studying fake news on social media. Big Data 8(3):171\u2013188","journal-title":"Big Data"},{"key":"10183_CR40","doi-asserted-by":"crossref","unstructured":"Shu K, Wang S, Liu H (2019) Beyond news contents: The role of social context for fake news detection. In: Proceedings of the twelfth ACM international conference on web search and data mining. ACM, pp 312\u2013320","DOI":"10.1145\/3289600.3290994"},{"issue":"3","key":"10183_CR41","first-page":"1264","volume":"47","author":"P Sibi","year":"2013","unstructured":"Sibi P, Allwyn Jones S, Siddarth P (2013) Analysis of different activation functions using back propagation neural networks. J Theor Appl Inf Technol 47(3):1264\u20131268","journal-title":"J Theor Appl Inf Technol"},{"key":"10183_CR42","unstructured":"Singh DSKR, Vivek RD, Ghosh I (2017) Automated fake news detection using linguistic analysis and machine learning. In: International conference on social computing, behavioral-cultural modeling, & prediction and behavior representation in modeling and simulation (SBP-BRiMS), pp 1\u20133"},{"key":"10183_CR43","unstructured":"Tacchini E, Ballarin G, Vedova ML, Moret S, Hoax Luca de Alfaro. (2017) Some like it Della Automated fake news detection in social networks. In: 2nd workshop on data science for social good, SoGood 2017. CEUR-WS, pp 1\u201315"},{"key":"10183_CR44","doi-asserted-by":"crossref","unstructured":"Tenney I, Das D, Pavlick E (2019) BERT rediscovers the classical NLP pipeline. In: Proceedings of the 57th annual meeting of the association for computational linguistics","DOI":"10.18653\/v1\/P19-1452"},{"key":"10183_CR45","unstructured":"Vasudevan V, Zoph B, Shlens J, Le QV (2019) Neural architecture search for convolutional neural networks. U.S Patent 10,521,729 issued December 31"},{"issue":"4","key":"10183_CR46","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3070644","volume":"11","author":"S Vosoughi","year":"2017","unstructured":"Vosoughi S, \u2019Neo Mohsenvand M, Roy D (2017) Rumor gauge: Predicting the veracity of rumors on Twitter. ACM Trans Knowl Discov Data (TKDD) 11(4):1\u201336","journal-title":"ACM Trans Knowl Discov Data (TKDD)"},{"key":"10183_CR47","doi-asserted-by":"crossref","unstructured":"Wang WY (2017) Liar, liar pants on fire: A new benchmark dataset for fake news detection. In: Proceedings of the 55th annual meeting of the association for computational linguistics (vol 2: short Papers), pp 422\u2013426","DOI":"10.18653\/v1\/P17-2067"},{"issue":"1","key":"10183_CR48","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s40979-019-0049-x","volume":"16","author":"AP Weiss","year":"2020","unstructured":"Weiss AP, Alwan A, Garcia EP, Garcia J (2020) Surveying fake news: Assessing university faculty\u2019s fragmented definition of fake news and its impact on teaching critical thinking. Int J Educ Integr 16(1):1\u201330","journal-title":"Int J Educ Integr"},{"key":"10183_CR49","doi-asserted-by":"crossref","unstructured":"Yang F, Liu Y, Xiaohui Y, Yang M (2012) Automatic detection of rumor on Sina Weibo. In: Proceedings of the ACM SIGKDD workshop on mining data semantics, pp 1\u20137","DOI":"10.1145\/2350190.2350203"},{"issue":"3","key":"10183_CR50","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1109\/MCI.2018.2840738","volume":"13","author":"T Young","year":"2018","unstructured":"Young T, Hazarika D, Poria S, Cambria E (2018) Recent trends in deep learning based natural language processing. IEEE Comput Intell Mag 13 (3):55\u201375","journal-title":"IEEE Comput Intell Mag"},{"key":"10183_CR51","unstructured":"Zhang X, Zhao J, LeCun Y (2015) Character-level convolutional networks for text classification. In: Advances in neural information processing systems, pp 649\u2013657"},{"key":"10183_CR52","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.aei.2019.02.009","volume":"40","author":"B Zhong","year":"2019","unstructured":"Zhong B, Xing X, Love P, Wang X u, Luo H (2019) Convolutional neural network: Deep learning-based classification of building quality problems. Adv Eng Inform 40:46\u201357","journal-title":"Adv Eng Inform"},{"key":"10183_CR53","unstructured":"Zhou X, Zafarani R (2018) Fake news: a survey of research, detection methods, and opportunities. arXiv:arXiv-1812"},{"issue":"2","key":"10183_CR54","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3161603","volume":"51","author":"A Zubiaga","year":"2018","unstructured":"Zubiaga A, Aker A, Bontcheva K, Liakata M, Procter R (2018) Detection and resolution of rumours in social media: A survey. ACM Comput Surv (CSUR) 51(2):1\u201336","journal-title":"ACM Comput Surv (CSUR)"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-10183-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-10183-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-10183-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T06:26:47Z","timestamp":1744180007000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-10183-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,7]]},"references-count":54,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2021,3]]}},"alternative-id":["10183"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-10183-2","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,7]]},"assertion":[{"value":"1 May 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 August 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 November 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 January 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}