{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:46:38Z","timestamp":1750308398456,"version":"3.41.0"},"reference-count":37,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2021,11,10]],"date-time":"2021-11-10T00:00:00Z","timestamp":1636502400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100004681","name":"Higher Education Commission (HEC), Pakistan","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100004681","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Center for Cyber Security"},{"name":"National Cyber Security Auditing and Evaluation Lab","award":["2(1078)\/HEC\/M&E\/2018\/707"],"award-info":[{"award-number":["2(1078)\/HEC\/M&E\/2018\/707"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2022,1,31]]},"abstract":"<jats:p>Increased connectivity has contributed greatly in facilitating rapid access to information and reliable communication. However, the uncontrolled information dissemination has also resulted in the spread of fake news. Fake news might be spread by a group of people or organizations to serve ulterior motives such as political or financial gains or to damage a country\u2019s public image. Given the importance of timely detection of fake news, the research area has intrigued researchers from all over the world. Most of the work for detecting fake news focuses on the English language. However, automated detection of fake news is important irrespective of the language used for spreading false information. Recognizing the importance of boosting research on fake news detection for low resource languages, this work proposes a novel semantically enriched technique to effectively detect fake news in Urdu\u2014a low resource language. A model based on deep contextual semantics learned from the convolutional neural network is proposed. The features learned from the convolutional neural network are combined with other n-gram-based features and are fed to a conventional majority voting ensemble classifier fitted with three base learners: Adaptive Boosting, Gradient Boosting, and Multi-Layer Perceptron. Experiments are performed with different models, and results show that enriching the traditional ensemble learner with deep contextual semantics along with other standard features shows the best results and outperforms the state-of-the-art Urdu fake news detection model.<\/jats:p>","DOI":"10.1145\/3461614","type":"journal-article","created":{"date-parts":[[2021,11,10]],"date-time":"2021-11-10T22:05:07Z","timestamp":1636581907000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Enriching Conventional Ensemble Learner with Deep Contextual Semantics to Detect Fake News in Urdu"],"prefix":"10.1145","volume":"21","author":[{"given":"Ramsha","family":"Saeed","sequence":"first","affiliation":[{"name":"National University of Sciences and Technology (NUST), Islamabad, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hammad","family":"Afzal","sequence":"additional","affiliation":[{"name":"National University of Sciences and Technology (NUST), Islamabad, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haider","family":"Abbas","sequence":"additional","affiliation":[{"name":"National University of Sciences and Technology (NUST), Islamabad, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maheen","family":"Fatima","sequence":"additional","affiliation":[{"name":"National University of Sciences and Technology (NUST), Islamabad, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,11,10]]},"reference":[{"key":"e_1_3_1_2_1","article-title":"Classification of fake news by fine-tuning deep bidirectional transformers based language model","author":"Aggarwal Akshay","year":"2020","unstructured":"Akshay Aggarwal, Aniruddha Chauhan, Deepika Kumar, Mamta Mittal, and Sharad Verma. 2020. Classification of fake news by fine-tuning deep bidirectional transformers based language model. EAI Endorsed Transactions on Scalable Information Systems 7, 17 (2020), 1\u201312.","journal-title":"EAI Endorsed Transactions on Scalable Information Systems"},{"key":"e_1_3_1_3_1","doi-asserted-by":"publisher","DOI":"10.5555\/1690299.1690305"},{"key":"e_1_3_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICITEED.2018.8534898"},{"key":"e_1_3_1_5_1","article-title":"Arabic fake news detection in social media using readers\u2019 comments: Text mining techniques in action","author":"Alanazi Sarah Saleh","year":"2020","unstructured":"Sarah Saleh Alanazi and Muhammad Badruddin Khan. 2020. Arabic fake news detection in social media using readers\u2019 comments: Text mining techniques in action. International Journal of Computer Science and Network Security 20, 9 (2020), 29\u201335.","journal-title":"International Journal of Computer Science and Network Security"},{"key":"e_1_3_1_6_1","first-page":"1","article-title":"\u201cBend the truth\u201d: Benchmark dataset for fake news detection in Urdu language and its evaluation","author":"Amjad Maaz","year":"2020","unstructured":"Maaz Amjad, Grigori Sidorov, Alisa Zhila, Helena G\u00f3mez-Adorno, Ilia Voronkov, and Alexander Gelbukh. 2020. \u201cBend the truth\u201d: Benchmark dataset for fake news detection in Urdu language and its evaluation. Journal of Intelligent & Fuzzy Systems.Preprint (2020), 1\u201313.","journal-title":"Journal of Intelligent & Fuzzy Systems."},{"key":"e_1_3_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2020.01.072"},{"key":"e_1_3_1_8_1","first-page":"2562","volume-title":"Proceedings of the 27th International Conference on Computational Linguistics.","author":"Zia Haris Bin","year":"2018","unstructured":"Haris Bin Zia, Agha Ali Raza, and Awais Athar. 2018. Urdu word segmentation using conditional random fields (CRFs). In Proceedings of the 27th International Conference on Computational Linguistics.2562\u20132569. http:\/\/aclweb.org\/anthology\/C18-1217."},{"key":"e_1_3_1_9_1","unstructured":"Aaron Blake. 2018. A new study suggests fake news might have won Donald Trump the 2016 election. Washington Post . Retrieved October 17 2021 from https:\/\/www.washingtonpost.com\/news\/the-fix\/wp\/2018\/04\/03\/a-new-study-suggests-fake-news-might-have-won-donald-trump-the-2016-election\/."},{"key":"e_1_3_1_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-04503-6_4"},{"key":"e_1_3_1_11_1","volume-title":"Stanford CS224d Deep Learning for NLP Final Project","author":"Chopra Sahil","year":"2017","unstructured":"Sahil Chopra, Saachi Jain, and John Merriman Sholar. 2017. Towards automatic identification of fake news: Headline-article stance detection with LSTM attention models. In Stanford CS224d Deep Learning for NLP Final Project."},{"key":"e_1_3_1_12_1","unstructured":"Jacobo L\u00f3pez Fern\u00e1ndez and Juan Antonio L\u00f3pez Ram\u0131rez. 2020. Approaches to the profiling fake news spreaders on Twitter task in English and Spanish. In Proceedings of the 2020 Conference and Labs of the Evaluation Forum (CLEF\u201920) ."},{"key":"e_1_3_1_13_1","unstructured":"Russell Goldman. 2016. Reading fake news Pakistani minister directs nuclear threat at Israel. New York Times . Retrieved October 17 2021 from https:\/\/www.nytimes.com\/2016\/12\/24\/world\/asia\/pakistan-israel-khawaja-asif-fake-news-nuclear.html."},{"key":"e_1_3_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/JEEIT.2019.8717386"},{"key":"e_1_3_1_15_1","first-page":"45","volume-title":"Proceedings of the 3rd International Workshop on Rumours and Deception in Social Media (RDSM\u201920)","author":"Kuzmin Gleb","year":"2020","unstructured":"Gleb Kuzmin, Daniil Larionov, Dina Pisarevskaya, and Ivan Smirnov. 2020. Fake news detection for the Russian language. In Proceedings of the 3rd International Workshop on Rumours and Deception in Social Media (RDSM\u201920). 45\u201357."},{"key":"e_1_3_1_16_1","unstructured":"Yunfei Long. 2017. Fake News Detection Through Multi-Perspective Speaker Profiles . Association for Computational Linguistics."},{"key":"e_1_3_1_17_1","unstructured":"Jing Ma Wei Gao and Kam-Fai Wong. 2017. Detect Rumors in Microblog Posts Using Propagation Structure via Kernel Learning . Association for Computational Linguistics."},{"key":"e_1_3_1_18_1","unstructured":"Jing Ma Wei Gao and Kam-Fai Wong. 2018. Rumor Detection on Twitter with Tree-Structured Recursive Neural Networks . Association for Computational Linguistics."},{"key":"e_1_3_1_19_1","article-title":"Efficient estimation of word representations in vector space","author":"Mikolov Tomas","year":"2013","unstructured":"Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. Arxiv Preprint arXiv:1301.3781 (2013).","journal-title":"Arxiv Preprint arXiv:1301.3781"},{"key":"e_1_3_1_20_1","article-title":"Fake news detection on social media using geometric deep learning","author":"Monti Federico","year":"2019","unstructured":"Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, and Michael M. Bronstein. 2019. Fake news detection on social media using geometric deep learning. Arxiv Preprint arXiv:1902.06673 (2019).","journal-title":"Arxiv Preprint arXiv:1902.06673"},{"key":"e_1_3_1_21_1","article-title":"Machine generation and detection of Arabic manipulated and fake news","author":"Nagoudi El Moatez Billah","year":"2020","unstructured":"El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed, Tariq Alhindi, and Hasan Cavusoglu. 2020. Machine generation and detection of Arabic manipulated and fake news. Arxiv Preprint arXiv:2011.03092 (2020).","journal-title":"Arxiv Preprint arXiv:2011.03092"},{"key":"e_1_3_1_22_1","article-title":"Finding deceptive opinion spam by any stretch of the imagination","author":"Ott Myle","year":"2011","unstructured":"Myle Ott, Yejin Choi, Claire Cardie, and Jeffrey T. Hancock. 2011. Finding deceptive opinion spam by any stretch of the imagination. Arxiv Preprint arXiv:1107.4557 (2011).","journal-title":"Arxiv Preprint arXiv:1107.4557"},{"key":"e_1_3_1_23_1","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-179034"},{"key":"e_1_3_1_24_1","doi-asserted-by":"publisher","DOI":"10.5555\/3304222.3304302"},{"key":"e_1_3_1_25_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1317"},{"key":"e_1_3_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132877"},{"key":"e_1_3_1_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-94105-9_3"},{"key":"e_1_3_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3137597.3137600"},{"key":"e_1_3_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIPR.2018.00092"},{"key":"e_1_3_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3290994"},{"key":"e_1_3_1_31_1","article-title":"Some like it hoax: Automated fake news detection in social networks","author":"Tacchini Eugenio","year":"2017","unstructured":"Eugenio Tacchini, Gabriele Ballarin, Marco L. Della Vedova, Stefano Moret, and Luca de Alfaro. 2017. Some like it hoax: Automated fake news detection in social networks. Arxiv Preprint arXiv:1704.07506 (2017).","journal-title":"Arxiv Preprint arXiv:1704.07506"},{"key":"e_1_3_1_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30760-8_25"},{"key":"e_1_3_1_33_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-2102"},{"key":"e_1_3_1_34_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.aap9559"},{"key":"e_1_3_1_35_1","article-title":"\u201cLiar, liar pants on fire\u201d: A new benchmark dataset for fake news detection","author":"Wang William Yang","year":"2017","unstructured":"William Yang Wang. 2017. \u201cLiar, liar pants on fire\u201d: A new benchmark dataset for fake news detection. Arxiv Preprint arXiv:1705.00648 (2017).","journal-title":"Arxiv Preprint arXiv:1705.00648"},{"key":"e_1_3_1_36_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015644"},{"key":"e_1_3_1_37_1","unstructured":"Kim Zetter. 2008. Six-year-old news story causes United Airlines stock to plummet\u2014UPDATE Google placed wrong date on story. Wired . Retrieved October 17 2021 from https:\/\/www.wired.com\/2008\/09\/six-year-old-st\/."},{"key":"e_1_3_1_38_1","article-title":"Fake news: A survey of research, detection methods, and opportunities","volume":"2","author":"Zhou Xinyi","year":"2018","unstructured":"Xinyi Zhou and Reza Zafarani. 2018. Fake news: A survey of research, detection methods, and opportunities. Arxiv Preprint arXiv:1812.00315 2 (2018).","journal-title":"Arxiv Preprint arXiv:1812.00315"}],"container-title":["ACM Transactions on Asian and Low-Resource Language Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3461614","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3461614","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T17:45:10Z","timestamp":1750268710000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3461614"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,10]]},"references-count":37,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,1,31]]}},"alternative-id":["10.1145\/3461614"],"URL":"https:\/\/doi.org\/10.1145\/3461614","relation":{},"ISSN":["2375-4699","2375-4702"],"issn-type":[{"type":"print","value":"2375-4699"},{"type":"electronic","value":"2375-4702"}],"subject":[],"published":{"date-parts":[[2021,11,10]]},"assertion":[{"value":"2020-11-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-04-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-11-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}