{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T10:24:15Z","timestamp":1776335055407,"version":"3.51.2"},"reference-count":39,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,10,17]],"date-time":"2020-10-17T00:00:00Z","timestamp":1602892800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2020,10,17]]},"abstract":"<jats:p>The advent of the World Wide Web and the rapid adoption of social media platforms (such as Facebook and Twitter) paved the way for information dissemination that has never been witnessed in the human history before. With the current usage of social media platforms, consumers are creating and sharing more information than ever before, some of which are misleading with no relevance to reality. Automated classification of a text article as misinformation or disinformation is a challenging task. Even an expert in a particular domain has to explore multiple aspects before giving a verdict on the truthfulness of an article. In this work, we propose to use machine learning ensemble approach for automated classification of news articles. Our study explores different textual properties that can be used to distinguish fake contents from real. By using those properties, we train a combination of different machine learning algorithms using various ensemble methods and evaluate their performance on 4 real world datasets. Experimental evaluation confirms the superior performance of our proposed ensemble learner approach in comparison to individual learners.<\/jats:p>","DOI":"10.1155\/2020\/8885861","type":"journal-article","created":{"date-parts":[[2020,10,18]],"date-time":"2020-10-18T01:05:07Z","timestamp":1602983107000},"page":"1-11","source":"Crossref","is-referenced-by-count":316,"title":["Fake News Detection Using Machine Learning Ensemble Methods"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7863-3746","authenticated-orcid":true,"given":"Iftikhar","family":"Ahmad","sequence":"first","affiliation":[{"name":"Department of Computer Science and Information Technology, University of Engineering and Technology, Peshawar, Pakistan"}]},{"given":"Muhammad","family":"Yousaf","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Technology, University of Engineering and Technology, Peshawar, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5388-0484","authenticated-orcid":true,"given":"Suhail","family":"Yousaf","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Technology, University of Engineering and Technology, Peshawar, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7885-0369","authenticated-orcid":true,"given":"Muhammad Ovais","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, Karlstad University, Karlstad, Sweden"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1177\/1081180X05284317"},{"key":"2","article-title":"Almost all the traffic to fake news sites is from facebook, new data show","author":"J. Wong","year":"2016"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1126\/science.aao2998"},{"issue":"5","key":"4","article-title":"The impact of term fake news on the scientific community scientific performance and mapping in web of science","volume":"9","author":"S. A. Garc\u00eda","year":"2020","journal-title":"Social Sciences"},{"key":"5","volume-title":"2016 Lie of the Year: Fake News","author":"A. D. Holan","year":"2016"},{"key":"6","article-title":"Fake News: Evidence from Financial Markets","author":"S. Kogan","year":"2019"},{"key":"7","first-page":"28","article-title":"Anatomy of a fake news scandal","volume":"1301","author":"A. Robb","year":"2017","journal-title":"Rolling Stone"},{"issue":"12","key":"8","article-title":"The long and brutal history of fake news","volume":"18","author":"J. Soll","year":"2016","journal-title":"Politico Magazine"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17072309"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1002\/pra2.2015.145052010082"},{"key":"11","article-title":"Misinfotext: a collection of news articles, with false and true labels","author":"F. T. Asr","year":"2019"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1145\/3137597.3137600"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1126\/science.aap9559"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1257\/jep.31.2.211"},{"key":"15","first-page":"7","article-title":"Fake news or truth? using satirical cues to detect potentially misleading news","author":"V. L. Rubin"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.3390\/app9194062"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-69155-8_9"},{"key":"18","volume-title":"Liar, Liar Pants on Fire: A New Benchmark Dataset for Fake News Detection","author":"W. Y. Wang","year":"2017"},{"key":"19","article-title":"A simple but tough-to-beat baseline for the fake news challenge stance detection task","author":"B. Riedel","year":"2017"},{"key":"20","first-page":"797","article-title":"Csi: a hybrid deep model for fake news detection","author":"N. Ruchansky"},{"key":"21","article-title":"Automatic detection of fake news","author":"V. P\u00e9rez-Rosas","year":"2017"},{"key":"22","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1007\/978-3-642-21551-3_33","article-title":"Bagging, boosting and ensemble methods","volume-title":"Handbook of Computational Statistics","author":"P. B\u00fchlmann","year":"2012"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1002\/spy2.9"},{"key":"24","volume-title":"Fake News","author":"Kaggle","year":"2018"},{"key":"25","volume-title":"Fake News Detection","author":"Kaggle","year":"2018"},{"key":"26","first-page":"281","article-title":"Random search for hyper-parameter optimization","volume":"13","author":"J. Bergstra","year":"2012","journal-title":"Journal of Machine Learning Research"},{"key":"27","volume-title":"The Discipline of Machine Learning","author":"T. M. Mitchell","year":"2006"},{"key":"28","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511801389","volume-title":"An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods","author":"N. Cristianini","year":"2000"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.1214\/009053607000000677"},{"key":"30","volume-title":"Support Vector Machines-An Introduction in \u201cSupport Vector Machines: Theory and Applications\u201d","author":"V. Kecman","year":"2005"},{"key":"31","doi-asserted-by":"publisher","DOI":"10.3390\/electronics9060963"},{"key":"32","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2004.04.008"},{"key":"33","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-016-9646-1"},{"key":"34","volume-title":"Classification and Regression Trees","author":"L. Breiman","year":"1984"},{"key":"35","first-page":"1401","article-title":"A brief introduction to boosting","volume":"99","author":"R. E. Schapire","year":"1999","journal-title":"IJCAI"},{"key":"36","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2008.11.003"},{"key":"37","first-page":"785","article-title":"Xgboost: a scalable tree boosting system","author":"T. Chen"},{"key":"38","doi-asserted-by":"publisher","DOI":"10.4310\/sii.2009.v2.n3.a8"},{"key":"39","doi-asserted-by":"publisher","DOI":"10.1109\/3468.618255"}],"container-title":["Complexity"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2020\/8885861.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2020\/8885861.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2020\/8885861.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,18]],"date-time":"2020-10-18T01:05:15Z","timestamp":1602983115000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/complexity\/2020\/8885861\/"}},"subtitle":[],"editor":[{"given":"M. Irfan","family":"Uddin","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2020,10,17]]},"references-count":39,"alternative-id":["8885861","8885861"],"URL":"https:\/\/doi.org\/10.1155\/2020\/8885861","relation":{},"ISSN":["1099-0526","1076-2787"],"issn-type":[{"value":"1099-0526","type":"electronic"},{"value":"1076-2787","type":"print"}],"subject":[],"published":{"date-parts":[[2020,10,17]]}}}