{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:57:00Z","timestamp":1758272220241,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031286933"},{"type":"electronic","value":"9783031286940"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-28694-0_51","type":"book-chapter","created":{"date-parts":[[2023,3,14]],"date-time":"2023-03-14T06:04:05Z","timestamp":1678773845000},"page":"546-557","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Identifying Fake News in the Russian-Ukrainian Conflict Using Machine Learning"],"prefix":"10.1007","author":[{"given":"Omar","family":"Darwish","sequence":"first","affiliation":[]},{"given":"Yahya","family":"Tashtoush","sequence":"additional","affiliation":[]},{"given":"Majdi","family":"Maabreh","sequence":"additional","affiliation":[]},{"given":"Rana","family":"Al-essa","sequence":"additional","affiliation":[]},{"given":"Ruba","family":"Aln\u2019uman","sequence":"additional","affiliation":[]},{"given":"Ammar","family":"Alqublan","sequence":"additional","affiliation":[]},{"given":"Munther","family":"Abualkibash","sequence":"additional","affiliation":[]},{"given":"Mahmoud","family":"Elkhodr","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,3,15]]},"reference":[{"key":"51_CR1","series-title":"Studies in Computational Intelligence","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-90087-8_1","volume-title":"Combating Fake News with Computational Intelligence Techniques","author":"M Lahby","year":"2022","unstructured":"Lahby, M., Aqil, S., Yafooz, W.M.S., Abakarim, Y.: Online fake news detection using machine learning techniques: a\u00a0systematic mapping study. In: Lahby, M., Pathan, A.S.K., Maleh, Y., Yafooz, W.M.S. (eds.) Combating Fake News with Computational Intelligence Techniques. SCI, vol. 1001, pp. 3\u201337. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-030-90087-8_1"},{"issue":"5","key":"51_CR2","doi-asserted-by":"publisher","first-page":"65","DOI":"10.3390\/data7050065","volume":"7","author":"Y Tashtoush","year":"2022","unstructured":"Tashtoush, Y., Alrababah, B., Darwish, O., Maabreh, M., Alsaedi, N.: A deep learning framework for detection of COVID-19 fake news on social media platforms. Data 7(5), 65 (2022)","journal-title":"Data"},{"key":"51_CR3","doi-asserted-by":"crossref","unstructured":"Mulahuwaish, A., Osti, M., Gyorick, K., Maabreh, M., Gupta, A., Qolomany, B.: CovidMis20: COVID-19 Misinformation Detection System on Twitter Tweets using Deep Learning Models. arXiv preprint arXiv:2209.05667 (2022)","DOI":"10.1007\/978-3-031-27199-1_47"},{"issue":"6","key":"51_CR4","doi-asserted-by":"publisher","first-page":"778","DOI":"10.14569\/IJACSA.2021.0120691","volume":"12","author":"AR Mahlous","year":"2021","unstructured":"Mahlous, A.R., Al-Laith, A.: Fake news detection in Arabic tweets during the COVID-19 pandemic. Int. J. Adv. Comput. Sci. Appl. 12(6), 778\u2013788 (2021). https:\/\/doi.org\/10.14569\/IJACSA.2021.0120691","journal-title":"Int. J. Adv. Comput. Sci. Appl."},{"key":"51_CR5","doi-asserted-by":"crossref","unstructured":"Helmstetter, S., Paulheim, H.: Weakly supervised learning for fake news detection on Twitter. In: 2018 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 274\u2013277. IEEE (2018)","DOI":"10.1109\/ASONAM.2018.8508520"},{"key":"51_CR6","doi-asserted-by":"crossref","unstructured":"Ajao, O., Bhowmik, D., Zargari, S.: 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. (2018)","DOI":"10.1145\/3217804.3217917"},{"key":"51_CR7","doi-asserted-by":"crossref","unstructured":"Aphiwongsophon, S., Chongstitvatana, P.: Detecting fake news with machine learning method. In: 2018 15th International Conference on Electrical Engineering\/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), pp. 528\u2013531. IEEE (2018)","DOI":"10.1109\/ECTICon.2018.8620051"},{"key":"51_CR8","unstructured":"Mahir, E.M., Akhter, S., Huq, M.R.: Detecting fake news using machine learning and deep learning algorithms. In: 2019 7th International Conference on Smart Computing & Communications (ICSCC), pp. 1\u20135. IEEE (2019)"},{"key":"51_CR9","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1007\/978-981-33-4367-2_28","volume-title":"Emerging Technologies in Data Mining and Information Security","author":"SBS Mugdha","year":"2021","unstructured":"Mugdha, S.B.S., et al.: A Gaussian naive Bayesian classifier for\u00a0fake news detection in Bengali. In: Hassanien, A.E., Bhattacharyya, S., Chakrabati, S., Bhattacharya, A., Dutta, S. (eds.) Emerging Technologies in Data Mining and Information Security. AISC, vol. 1300, pp. 283\u2013291. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-33-4367-2_28"},{"key":"51_CR10","doi-asserted-by":"crossref","unstructured":"Kaliyar, Rohit Kumar. \u201cFake news detection using a deep neural network.\u201c In 2018 4th International Conference on Computing Communication and Automation (ICCCA), pp. 1\u20137. IEEE, 2018","DOI":"10.1109\/CCAA.2018.8777343"},{"issue":"2","key":"51_CR11","doi-asserted-by":"publisher","first-page":"969","DOI":"10.1007\/s00521-021-06230-0","volume":"34","author":"A Zervopoulos","year":"2021","unstructured":"Zervopoulos, A., Alvanou, A.G., Bezas, K., Papamichail, A., Maragoudakis, M., Kermanidis, K.: Deep learning for fake news detection on twitter regarding the 2019 Hong Kong protests. Neural Comput. Appl. 34(2), 969\u2013982 (2021). https:\/\/doi.org\/10.1007\/s00521-021-06230-0","journal-title":"Neural Comput. Appl."},{"issue":"2","key":"51_CR12","doi-asserted-by":"crossref","first-page":"e3767","DOI":"10.1002\/ett.3767","volume":"31","author":"S Kumar","year":"2020","unstructured":"Kumar, S., Asthana, R., Upadhyay, S., Upreti, N., Akbar, M.: Fake news detection using deep learning models: A novel approach. Trans. Emerging Telecommun. Technol. 31(2), e3767 (2020)","journal-title":"Trans. Emerging Telecommun. Technol."},{"key":"51_CR13","doi-asserted-by":"crossref","unstructured":"Kareem, I., Awan, S.M.: Pakistani media fake news classification using machine learning classifiers. In: 2019 International Conference on Innovative Computing (ICIC), pp. 1\u20136. IEEE (2019)","DOI":"10.1109\/ICIC48496.2019.8966734"},{"issue":"1","key":"51_CR14","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1145\/234313.234346","volume":"28","author":"JR Quinlan","year":"1996","unstructured":"Quinlan, J.R.: Learning decision tree classifiers. ACM Comput. Surv. 28(1), 71\u201372 (1996). https:\/\/doi.org\/10.1145\/234313.234346","journal-title":"ACM Comput. Surv."},{"issue":"2","key":"51_CR15","first-page":"38","volume":"14","author":"K Yazdi","year":"2020","unstructured":"Yazdi, K., et al.: Improving fake news detection using k-means and support vector machine approaches. Int. J. Electron. Commun. Eng. 14(2), 38\u201342 (2020)","journal-title":"Int. J. Electron. Commun. Eng."},{"key":"51_CR16","unstructured":"Poovaraghan, R. J., Keerti Priya, M.V., Sai Surya Vamsi, P.V., Mewara, M., Loganathan, S.: Fake news accuracy using naive bayes classifier. Int. J. Recent Technol. Eng. (IJRTE). 8(1C2), 2277\u20133878 (2019)"},{"key":"51_CR17","unstructured":"Kuang, Q., Zhao, L.: A practical GPU based kNN algorithm. In: Proceedings of The 2009 International Symposium on Computer Science and Computational Technology (ISCSCI 2009), p. 151. Academy Publisher (2009)"},{"key":"51_CR18","doi-asserted-by":"crossref","unstructured":"Ray, S.: A quick review of machine learning algorithms. In: 2019 International conference on machine learning, big data, cloud and parallel computing (COMITCon), pp. 35\u201339. IEEE (2019)","DOI":"10.1109\/COMITCon.2019.8862451"},{"issue":"3","key":"51_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3439726","volume":"54","author":"S Minaee","year":"2021","unstructured":"Minaee, S., Kalchbrenner, N., Cambria, E., Nikzad, N., Chenaghlu, M., Gao, J.: Deep learning\u2013based text classification: a comprehensive review. ACM Comput. Surv. (CSUR) 54(3), 1\u201340 (2021)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"51_CR20","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown, T., et al.: Language models are few-shot learners. Adv. Neural Inf. Process. Syst. 33, 1877\u20131901 (2020)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"51_CR21","unstructured":"Lepikhin, D., et al.: Scaling giant models with conditional computation and automatic sharding. arXiv preprint arXiv:2006.16668 (2020)"},{"key":"51_CR22","doi-asserted-by":"crossref","unstructured":"Jing, L.-Pi., Huang, H.-K., Shi, H.-B.: Improved feature selection approach TFIDF in text mining. In: Proceedings. International Conference on Machine Learning and Cybernetics, vol. 2, pp. 944\u2013946. IEEE (2002)","DOI":"10.1109\/ICMLC.2002.1174522"},{"key":"51_CR23","unstructured":"Barathi Ganesh, H.B., Anand Kumar, M., Soman, K.P.: Distributional semantic representation for text classification and information retrieval. In: FIRE (Working Notes), pp. 126\u2013130 (2016)"},{"key":"51_CR24","unstructured":"Grandini, M., Bagli, E., Visani, G.: Metrics for multi-class classification: an overview. arXiv preprint arXiv:2008.05756 (2020)"}],"container-title":["Lecture Notes in Networks and Systems","Advanced Information Networking and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-28694-0_51","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,16]],"date-time":"2024-10-16T09:23:14Z","timestamp":1729070594000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-28694-0_51"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031286933","9783031286940"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-28694-0_51","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"15 March 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AINA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Information Networking and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Juiz de Fora","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brazil","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 March 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 March 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"37","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aina2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/voyager.ce.fit.ac.jp\/conf\/aina\/2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}