{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T16:49:47Z","timestamp":1772556587992,"version":"3.50.1"},"reference-count":63,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,3,20]],"date-time":"2025-03-20T00:00:00Z","timestamp":1742428800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,3,20]],"date-time":"2025-03-20T00:00:00Z","timestamp":1742428800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soc. Netw. Anal. Min."],"DOI":"10.1007\/s13278-025-01412-3","type":"journal-article","created":{"date-parts":[[2025,3,20]],"date-time":"2025-03-20T02:14:13Z","timestamp":1742436853000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["ScrutNet: a deep ensemble network for detecting fake news in online text"],"prefix":"10.1007","volume":"15","author":[{"given":"Aryan","family":"Verma","sequence":"first","affiliation":[]},{"given":"P.","family":"Priyanka","sequence":"additional","affiliation":[]},{"given":"Tayyab","family":"Khan","sequence":"additional","affiliation":[]},{"given":"Karan","family":"Singh","sequence":"additional","affiliation":[]},{"given":"Lawal .O.","family":"Yesufu","sequence":"additional","affiliation":[]},{"given":"Mazeyanti Mohd","family":"Ariffin","sequence":"additional","affiliation":[]},{"given":"Ali","family":"Ahmadian","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,3,20]]},"reference":[{"key":"1412_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s42979-020-00165-4","volume":"1","author":"A Agarwal","year":"2020","unstructured":"Agarwal A, Mittal M, Pathak A, Goyal LM (2020) Fake news detection using a blend of neural networks: an application of deep learning. SN Comput Sci 1:1\u20139","journal-title":"SN Comput Sci"},{"key":"1412_CR2","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/8885861","author":"I Ahmad","year":"2020","unstructured":"Ahmad I, Ahmad I, Ahmad I, Ahmad I, Yousaf MM, Yousaf M, Yousaf S, Yousaf S, Ahmad MO, Ahmad MO (2020) Fake news detection using machine learning ensemble methods. Complexity. https:\/\/doi.org\/10.1155\/2020\/8885861","journal-title":"Complexity"},{"issue":"1","key":"1412_CR3","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1002\/spy2.9","volume":"1","author":"H Ahmed","year":"2018","unstructured":"Ahmed H, Traore I, Saad S (2018) Detecting opinion spams and fake news using text classification. Securi Priv 1(1):9","journal-title":"Securi Priv"},{"key":"1412_CR4","doi-asserted-by":"crossref","unstructured":"Ajao O, Bhowmik D, Zargari S (2019) Sentiment aware fake news detection on online social networks. In: ICASSP 2019-2019 IEEE international conference on acoustics, speech and signal processing (ICASSP), IEEE, pp 2507\u20132511","DOI":"10.1109\/ICASSP.2019.8683170"},{"key":"1412_CR5","doi-asserted-by":"crossref","unstructured":"Ajao O, Bhowmik D, Zargari S (2018) Fake news identification on twitter with hybrid CNN and RNN models. In: Proceedings of the 9th international conference on social media and society, pp 226\u2013230","DOI":"10.1145\/3217804.3217917"},{"issue":"2","key":"1412_CR6","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\u2013236","journal-title":"J Econ Perspect"},{"key":"1412_CR7","doi-asserted-by":"publisher","first-page":"10813","DOI":"10.1007\/s13369-020-04839-2","volume":"45","author":"A Alsaeedi","year":"2020","unstructured":"Alsaeedi A, Al-Sarem M (2020) Detecting rumors on social media based on a CNN deep learning technique. Arab J Sci Eng 45:10813\u201310844","journal-title":"Arab J Sci Eng"},{"key":"1412_CR8","doi-asserted-by":"publisher","first-page":"4315","DOI":"10.1007\/s12652-019-01527-4","volume":"12","author":"MZ Asghar","year":"2021","unstructured":"Asghar MZ, Habib A, Habib A, Khan A, Ali R, Khattak A (2021) Exploring deep neural networks for rumor detection. J Ambient Intell Humaniz Comput 12:4315\u20134333","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"1412_CR9","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1016\/j.procs.2020.01.072","volume":"165","author":"P Bahad","year":"2019","unstructured":"Bahad P, Saxena P, Kamal R (2019) Fake news detection using bi-directional LSTM-recurrent neural network. Proced Comput Sci 165:74\u201382","journal-title":"Proced Comput Sci"},{"key":"1412_CR10","doi-asserted-by":"crossref","unstructured":"Bhutani B, Rastogi N, Sehgal P, Purwar A (2019) Fake news detection using sentiment analysis. In: 2019 twelfth international conference on contemporary computing (IC3), IEEE, pp 1\u20135","DOI":"10.1109\/IC3.2019.8844880"},{"issue":"6","key":"1412_CR11","doi-asserted-by":"publisher","first-page":"6581","DOI":"10.1007\/s40747-023-01098-0","volume":"9","author":"E Essa","year":"2023","unstructured":"Essa E, Omar K, Alqahtani A (2023) Fake news detection based on a hybrid BERT and lightGBM models. Complex Intell Syst 9(6):6581\u20136592","journal-title":"Complex Intell Syst"},{"key":"1412_CR12","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez-Reyes FC, Shinde S (2018) Evaluating deep neural networks for automatic fake news detection in political domain. In: Advances in artificial intelligence-IBERAMIA 2018: 16th Ibero-American Conference on AI, Trujillo, Peru, November 13-16, 2018, Proceedings 16. Springer, pp 206\u2013216","DOI":"10.1007\/978-3-030-03928-8_17"},{"issue":"2","key":"1412_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3381750","volume":"20","author":"B Ghanem","year":"2020","unstructured":"Ghanem B, Rosso P, Rangel F (2020) An emotional analysis of false information in social media and news articles. ACM Trans Internet Technol 20(2):1\u201318","journal-title":"ACM Trans Internet Technol"},{"key":"1412_CR14","doi-asserted-by":"crossref","unstructured":"Giachanou A, Rosso P, Crestani F (2019) Leveraging emotional signals for credibility detection. In: Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval, pp 877\u2013880","DOI":"10.1145\/3331184.3331285"},{"key":"1412_CR15","doi-asserted-by":"crossref","unstructured":"Girgis S, Amer E, Gadallah M (2018) Deep learning algorithms for detecting fake news in online text. In: 2018 13th international conference on computer engineering and systems (ICCES), IEEE, pp 93\u201397","DOI":"10.1109\/ICCES.2018.8639198"},{"key":"1412_CR16","doi-asserted-by":"crossref","unstructured":"Granik M, Mesyura V (2017) Fake news detection using Naive Bayes classifier. In: 2017 IEEE first Ukraine conference on electrical and computer engineering (UKRCON), IEEE, pp 900\u2013903","DOI":"10.1109\/UKRCON.2017.8100379"},{"key":"1412_CR17","doi-asserted-by":"crossref","unstructured":"Guleria V, Verma A, Dhenkawat R, Chaurasia U, Singh NP (2023) Brain tumor detection using texture based LBP feature on MRI images using feature selection technique. In: Artificial intelligence, blockchain, computing and security, vol 1, CRC Press, pp 30\u201336","DOI":"10.1201\/9781003393580-6"},{"key":"1412_CR18","doi-asserted-by":"crossref","unstructured":"Ibrishimova MD, Li KF (2020) A machine learning approach to fake news detection using knowledge verification and natural language processing. In: Advances in intelligent networking and collaborative systems: the 11th international conference on intelligent networking and collaborative systems (INCoS-2019), Springer, pp 223\u2013234","DOI":"10.1007\/978-3-030-29035-1_22"},{"issue":"12","key":"1412_CR19","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.1080\/08839514.2019.1661579","volume":"33","author":"SS Jadhav","year":"2019","unstructured":"Jadhav SS, Thepade SD (2019) Fake news identification and classification using DSSM and improved recurrent neural network classifier. Appl Artif Intell 33(12):1058\u20131068","journal-title":"Appl Artif Intell"},{"key":"1412_CR20","doi-asserted-by":"publisher","unstructured":"Jain P, Jain P, Jain P, Sharma S, Sharma S, Sharma S, Monica N, Monica N, M\u00c3\u00b4nica M, Aggarwal PK, Aggarwal PK, Aggarwal P (2022) Classifying fake news detection using SVM, Naive Bayes and lSTM. Confluence https:\/\/doi.org\/10.1109\/confluence52989.2022.9734129","DOI":"10.1109\/confluence52989.2022.9734129"},{"key":"1412_CR21","doi-asserted-by":"publisher","unstructured":"Jaiswal A, Verma H, Sachdeva N (2023) Swarm optimized fake news detection on social-media textual content using deep learning. 2023 international conference on advances in computing, communication and applied informatics (ACCAI) https:\/\/doi.org\/10.1109\/accai58221.2023.10201229","DOI":"10.1109\/accai58221.2023.10201229"},{"key":"1412_CR22","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1016\/j.chb.2017.11.034","volume":"80","author":"SM Jang","year":"2018","unstructured":"Jang SM, Kim JK (2018) Third person effects of fake news: fake news regulation and media literacy interventions. Comput Hum Behav 80:295\u2013302","journal-title":"Comput Hum Behav"},{"key":"1412_CR23","unstructured":"Jazi SY, Mirzaeinia A, Jazi SY (2024) Analyzing gender polarity in short social media texts with BERT: the role of emojis and emoticons. arXiv preprint arXiv:2406.09573"},{"issue":"8","key":"1412_CR24","doi-asserted-by":"publisher","first-page":"11765","DOI":"10.1007\/s11042-020-10183-2","volume":"80","author":"RK Kaliyar","year":"2021","unstructured":"Kaliyar RK, Goswami A, Narang P (2021) FakeBERT: fake news detection in social media with a BERT-based deep learning approach. Multimed Tools Appl 80(8):11765\u201311788","journal-title":"Multimed Tools Appl"},{"key":"1412_CR25","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) FNDNet-a deep convolutional neural network for fake news detection. Cogn Syst Res 61:32\u201344","journal-title":"Cogn Syst Res"},{"key":"1412_CR26","doi-asserted-by":"crossref","unstructured":"Kaliyar RK (2018) Fake news detection using a deep neural network. In: 2018 4th International conference on computing communication and automation (ICCCA), IEEE, pp 1\u20137","DOI":"10.1109\/CCAA.2018.8777343"},{"key":"1412_CR27","doi-asserted-by":"publisher","first-page":"14918","DOI":"10.1109\/ACCESS.2024.3354165","volume":"12","author":"GK Koru","year":"2024","unstructured":"Koru GK, Uluyol \u00c7 (2024) Detection of Turkish fake news from tweets with BERT models. IEEE Access 12:14918\u201314931","journal-title":"IEEE Access"},{"key":"1412_CR28","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1007\/s00779-019-01289-y","volume":"24","author":"Q Li","year":"2020","unstructured":"Li Q, Hu Q, Lu Y, Yang Y, Cheng J (2020) Multi-level word features based on CNN for fake news detection in cultural communication. Pers Ubiquit Comput 24:259\u2013272","journal-title":"Pers Ubiquit Comput"},{"key":"1412_CR29","unstructured":"Long Y, Lu Q, Xiang R, Li M, Huang C-R (2017) Fake news detection through multi-perspective speaker profiles. In: Proceedings of the eighth international joint conference on natural language processing (volume 2: short papers), pp 252\u2013256"},{"issue":"6","key":"1412_CR30","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1002\/spy2.264","volume":"5","author":"M Madani","year":"2022","unstructured":"Madani M, Motameni H, Mohamadi H (2022) Fake news detection using deep learning integrating feature extraction, natural language processing, and statistical descriptors. Secur Priv 5(6):264","journal-title":"Secur Priv"},{"key":"1412_CR31","unstructured":"Mahir EM, Akhter S, Huq MR, et al (2019) Detecting fake news using machine learning and deep learning algorithms. In: 2019 7th international conference on smart computing and communications (ICSCC), IEEE, pp 1\u20135"},{"key":"1412_CR32","doi-asserted-by":"crossref","unstructured":"Mandical RR, Mamatha N, Shivakumar N, Monica R, Krishna A (2020) Identification of fake news using machine learning. In: 2020 IEEE international conference on electronics, computing and communication technologies (CONECCT), IEEE, pp 1\u20136","DOI":"10.1109\/CONECCT50063.2020.9198610"},{"key":"1412_CR33","doi-asserted-by":"crossref","unstructured":"Manzoor SI, Singla J, et al (2019) Fake news detection using machine learning approaches: a systematic review. In: 2019 3rd international conference on trends in electronics and informatics (ICOEI), IEEE, pp 230\u2013234","DOI":"10.1109\/ICOEI.2019.8862770"},{"key":"1412_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2022\/1575365","volume":"2022","author":"S Mishra","year":"2022","unstructured":"Mishra S, Shukla P, Agarwal R (2022) Analyzing machine learning enabled fake news detection techniques for diversified datasets. Wirel Commun Mob Comput 2022:1\u201318","journal-title":"Wirel Commun Mob Comput"},{"key":"1412_CR35","doi-asserted-by":"publisher","first-page":"156151","DOI":"10.1109\/ACCESS.2021.3129329","volume":"9","author":"MF Mridha","year":"2021","unstructured":"Mridha MF, Keya AJ, Hamid MA, Monowar MM, Rahman MS (2021) A comprehensive review on fake news detection with deep learning. IEEE Access 9:156151\u2013156170","journal-title":"IEEE Access"},{"issue":"1","key":"1412_CR36","first-page":"100007","volume":"1","author":"JA Nasir","year":"2021","unstructured":"Nasir JA, Khan OS, Varlamis I (2021) Fake news detection: a hybrid CNN-RNN based deep learning approach. Int J Inf Manage Data Insights 1(1):100007","journal-title":"Int J Inf Manage Data Insights"},{"key":"1412_CR37","doi-asserted-by":"publisher","first-page":"123174","DOI":"10.1016\/j.physa.2019.123174","volume":"540","author":"FA Ozbay","year":"2020","unstructured":"Ozbay FA, Alatas B (2020) Fake news detection within online social media using supervised artificial intelligence algorithms. Phys A 540:123174","journal-title":"Phys A"},{"key":"1412_CR38","doi-asserted-by":"crossref","unstructured":"Padnekar SM, Kumar GS, Deepak P (2020) BiLSTM-autoencoder architecture for stance prediction. In: 2020 international conference on data science and engineering (ICDSE), IEEE, pp 1\u20135","DOI":"10.1109\/ICDSE50459.2020.9310133"},{"key":"1412_CR39","doi-asserted-by":"publisher","DOI":"10.1109\/access.2023.3294613","author":"MJ Park","year":"2023","unstructured":"Park MJ, Chai S (2023) Constructing a user-centered fake news detection model by using classification algorithms in machine learning techniques. IEEE Access. https:\/\/doi.org\/10.1109\/access.2023.3294613","journal-title":"IEEE Access"},{"issue":"5","key":"1412_CR40","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1016\/j.tics.2021.02.007","volume":"25","author":"G Pennycook","year":"2021","unstructured":"Pennycook G, Rand DG (2021) The psychology of fake news. Trends Cogn Sci 25(5):388\u2013402","journal-title":"Trends Cogn Sci"},{"key":"1412_CR41","doi-asserted-by":"crossref","unstructured":"Qawasmeh E, Tawalbeh M, Abdullah M (2019) Automatic identification of fake news using deep learning. In: 2019 sixth international conference on social networks analysis, management and security (SNAMS), IEEE, pp 383\u2013388","DOI":"10.1109\/SNAMS.2019.8931873"},{"key":"1412_CR42","doi-asserted-by":"crossref","unstructured":"Rasool T, Butt WH, Shaukat A, Akram MU (2019) Multi-label fake news detection using multi-layered supervised learning. In: Proceedings of the 2019 11th international conference on computer and automation engineering, pp 73\u201377","DOI":"10.1145\/3313991.3314008"},{"issue":"2","key":"1412_CR43","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1007\/s11633-019-1216-5","volume":"17","author":"H Reddy","year":"2020","unstructured":"Reddy H, Raj N, Gala M, Basava A (2020) Text-mining-based fake news detection using ensemble methods. Int J Autom Comput 17(2):210\u2013221","journal-title":"Int J Autom Comput"},{"key":"1412_CR44","doi-asserted-by":"crossref","unstructured":"Rusli A, Young JC, Iswari NMS (2020) Identifying fake news in Indonesian via supervised binary text classification. In: 2020 IEEE international conference on industry 4.0, artificial intelligence, and communications technology (IAICT), IEEE, pp 86\u201390","DOI":"10.1109\/IAICT50021.2020.9172020"},{"key":"1412_CR45","doi-asserted-by":"publisher","first-page":"106983","DOI":"10.1016\/j.asoc.2020.106983","volume":"100","author":"SR Sahoo","year":"2021","unstructured":"Sahoo SR, Gupta BB (2021) Multiple features based approach for automatic fake news detection on social networks using deep learning. Appl Soft Comput 100:106983","journal-title":"Appl Soft Comput"},{"key":"1412_CR46","doi-asserted-by":"crossref","unstructured":"Shaik S (2023) A review and analysis on fake news detection based on artificial intelligence and data science. Tuijin Jishu J Propuls Technol. https:\/\/doi.org\/10.52783\/tjjpt.v44.i3.2107","DOI":"10.52783\/tjjpt.v44.i3.2107"},{"key":"1412_CR47","doi-asserted-by":"crossref","unstructured":"Singh S, Verma A, Guleria V, Yadav S, Singh NP (2023) Deep learning-based networks to detect leaf disease in maize and corn. In: 2023 international conference on IoT, communication and automation technology (ICICAT), IEEE, pp 1\u20136","DOI":"10.1109\/ICICAT57735.2023.10263746"},{"key":"1412_CR48","doi-asserted-by":"crossref","unstructured":"Singhania S, Fernandez N, Rao S (2017) 3han: a deep neural network for fake news detection. In: Neural information processing: 24th international conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, proceedings, Part II 24, Springer, pp 572\u2013581","DOI":"10.1007\/978-3-319-70096-0_59"},{"issue":"3","key":"1412_CR49","first-page":"10","volume":"1","author":"A Thota","year":"2018","unstructured":"Thota A, Tilak P, Ahluwalia S, Lohia N (2018) Fake news detection: a deep learning approach. SMU Data Sci Rev 1(3):10","journal-title":"SMU Data Sci Rev"},{"key":"1412_CR50","doi-asserted-by":"publisher","DOI":"10.3390\/electronics12173676","author":"CM Tsai","year":"2023","unstructured":"Tsai CM (2023) Stylometric fake news detection based on natural language processing using named entity recognition: in-domain and cross-domain analysis. Electronics. https:\/\/doi.org\/10.3390\/electronics12173676","journal-title":"Electronics"},{"key":"1412_CR51","unstructured":"Ujgare NS, Singh NP, Verma PK, Patil M, Verma A. Non-invasive blood group prediction using optimized EfficientNet architecture: a systematic approach"},{"key":"1412_CR52","doi-asserted-by":"publisher","first-page":"156695","DOI":"10.1109\/ACCESS.2020.3019735","volume":"8","author":"M Umer","year":"2020","unstructured":"Umer M, Imtiaz Z, Ullah S, Mehmood A, Choi GS, On B-W (2020) Fake news stance detection using deep learning architecture (CNN-LSTM). IEEE Access 8:156695\u2013156706","journal-title":"IEEE Access"},{"key":"1412_CR53","doi-asserted-by":"publisher","unstructured":"Ushashree P, Naik A, Gurav S, Kumar A, Chethan SR, Madhumala BS (2023) Fake news detection using neural network. 2023. In: IEEE international conference on integrated circuits and communication systems (ICICACS) https:\/\/doi.org\/10.1109\/icicacs57338.2023.10100208","DOI":"10.1109\/icicacs57338.2023.10100208"},{"key":"1412_CR54","doi-asserted-by":"crossref","unstructured":"Vardhan H, Verma A, Singh NP (2023) An ensemble learning approach for large scale birds species classification. In: Artificial intelligence, blockchain, computing and security, vol 1, CRC Press, pp 3\u20138","DOI":"10.1201\/9781003393580-1"},{"issue":"8","key":"1412_CR55","doi-asserted-by":"publisher","first-page":"10617","DOI":"10.1007\/s12652-022-04338-2","volume":"14","author":"PK Verma","year":"2023","unstructured":"Verma PK, Agrawal P, Madaan V, Prodan R (2023) MCred: multi-modal message credibility for fake news detection using BERT and CNN. J Ambient Intell Humaniz Comput 14(8):10617\u201310629","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"1412_CR56","doi-asserted-by":"publisher","first-page":"105298","DOI":"10.1016\/j.compbiomed.2022.105298","volume":"143","author":"A Verma","year":"2022","unstructured":"Verma A, Amin SB, Naeem M, Saha M (2022) Detecting COVID-19 from chest computed tomography scans using AI-driven android application. Comput Biol Med 143:105298","journal-title":"Comput Biol Med"},{"issue":"6","key":"1412_CR57","doi-asserted-by":"publisher","first-page":"840","DOI":"10.1007\/s42979-023-02308-9","volume":"4","author":"A Verma","year":"2023","unstructured":"Verma A, Gupta N, Bhatele P, Khanna P (2023) JMCD dataset for brain tumor detection and analysis using explainable deep learning. SN Comput Sci 4(6):840","journal-title":"SN Comput Sci"},{"issue":"3","key":"1412_CR58","first-page":"1453","volume":"15","author":"A Verma","year":"2023","unstructured":"Verma A, Rahi R, Singh NP (2023) Novel ALBP and OLBP features for gender prediction from offline handwriting. Int J Inf Technol 15(3):1453\u20131464","journal-title":"Int J Inf Technol"},{"issue":"19","key":"1412_CR59","doi-asserted-by":"publisher","first-page":"57511","DOI":"10.1007\/s11042-023-17813-5","volume":"83","author":"A Verma","year":"2024","unstructured":"Verma A, Singh N, Khanna V, Singh BP, Singh NP (2024) Automated tongue contour extraction from ultrasound sequences using signal enhancing neural network and energy minimized spline. Multimed Tools Appl 83(19):57511\u201357530","journal-title":"Multimed Tools Appl"},{"key":"1412_CR60","unstructured":"Veronica P-R, Bennett K, Alexandra L, Rada M (2018) Automatic detection of fake news. In: International conference on computational linguistics (COLING)"},{"key":"1412_CR61","doi-asserted-by":"crossref","unstructured":"Yousefpanah K, Ebadi M, Sabzekar S, Zakaria NH, Osman NA, Ahmadian A (2024) An emerging network for COVID-19 CT-scan classification using an ensemble deep transfer learning model. Acta Tropica 107277","DOI":"10.1016\/j.actatropica.2024.107277"},{"issue":"2","key":"1412_CR62","doi-asserted-by":"publisher","first-page":"102025","DOI":"10.1016\/j.ipm.2019.03.004","volume":"57","author":"X Zhang","year":"2020","unstructured":"Zhang X, Ghorbani AA (2020) An overview of online fake news: characterization, detection, and discussion. Inf Process Manage 57(2):102025","journal-title":"Inf Process Manage"},{"key":"1412_CR63","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.patrec.2024.02.014","volume":"180","author":"Z Zhang","year":"2024","unstructured":"Zhang Z, Lv Q, Jia X, Yun W, Miao G, Mao Z, Wu G (2024) GBCA: graph convolution network and BERT combined with co-attention for fake news detection. Pattern Recogn Lett 180:26\u201332","journal-title":"Pattern Recogn Lett"}],"container-title":["Social Network Analysis and Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-025-01412-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13278-025-01412-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13278-025-01412-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T08:29:19Z","timestamp":1765960159000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13278-025-01412-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,20]]},"references-count":63,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1412"],"URL":"https:\/\/doi.org\/10.1007\/s13278-025-01412-3","relation":{},"ISSN":["1869-5469"],"issn-type":[{"value":"1869-5469","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,20]]},"assertion":[{"value":"2 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 January 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 February 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 March 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors of this research work declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"21"}}