{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T11:05:36Z","timestamp":1762254336983,"version":"3.40.3"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031208584"},{"type":"electronic","value":"9783031208591"}],"license":[{"start":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T00:00:00Z","timestamp":1670889600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,13]],"date-time":"2022-12-13T00:00:00Z","timestamp":1670889600000},"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\/978-3-031-20859-1_13","type":"book-chapter","created":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T08:07:02Z","timestamp":1670832422000},"page":"121-130","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Multi-policy Framework for Deep Learning-based Fake News Detection"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4968-3653","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Vitorino","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1693-7872","authenticated-orcid":false,"given":"Tiago","family":"Dias","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5592-3107","authenticated-orcid":false,"given":"Tiago","family":"Fonseca","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5030-7751","authenticated-orcid":false,"given":"Nuno","family":"Oliveira","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2519-9859","authenticated-orcid":false,"given":"Isabel","family":"Pra\u00e7a","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,12,13]]},"reference":[{"issue":"2","key":"13_CR1","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1257\/jep.31.2.187","volume":"31","author":"EL Groshen","year":"2017","unstructured":"Groshen, E.L., Moyer, B.C., Aizcorbe, A.M., Bradley, R., Friedman, D.M.: How government statistics adjust for potential biases from quality change and new goods in an age of digital technologies: a view from the trenches. J. Econ. Perspect. 31(2), 187\u2013210 (2017). https:\/\/doi.org\/10.1257\/jep.31.2.187","journal-title":"J. Econ. Perspect."},{"key":"13_CR2","doi-asserted-by":"publisher","first-page":"156151","DOI":"10.1109\/ACCESS.2021.3129329","volume":"9","author":"MF Mridha","year":"2021","unstructured":"Mridha, M.F., Keya, A.J., Hamid, M.A., Monowar, M.M., Rahman, M.S.: A Comprehensive review on fake news detection with deep learning. IEEE Access 9, 156151\u2013156170 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2021.3129329","journal-title":"IEEE Access"},{"issue":"3","key":"13_CR3","doi-asserted-by":"publisher","first-page":"430","DOI":"10.1177\/0093650212453600","volume":"41","author":"M Balmas","year":"2014","unstructured":"Balmas, M.: When fake news becomes real: combined exposure to multiple news sources and political attitudes of inefficacy, alienation, and cynicism. Communic. Res. 41(3), 430\u2013454 (2014). https:\/\/doi.org\/10.1177\/0093650212453600","journal-title":"Communic. Res."},{"issue":"7","key":"13_CR4","doi-asserted-by":"publisher","first-page":"891","DOI":"10.1080\/17512786.2016.1163237","volume":"10","author":"I Khaldarova","year":"2016","unstructured":"Khaldarova, I., Pantti, M.: Fake news: the narrative battle over the Ukrainian conflict. J. Pract. 10(7), 891\u2013901 (2016). https:\/\/doi.org\/10.1080\/17512786.2016.1163237","journal-title":"J. Pract."},{"doi-asserted-by":"publisher","unstructured":"Uppal, A., Sachdeva, V., Sharma, S.: Fake news detection using discourse segment structure analysis. In: Proceedings of the Confluence 2020 - 10th International Conference on Cloud Computing, Data Science and Engineering, pp. 751\u2013756 (2020). https:\/\/doi.org\/10.1109\/Confluence47617.2020.9058106","key":"13_CR5","DOI":"10.1109\/Confluence47617.2020.9058106"},{"issue":"1","key":"13_CR6","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1145\/3137597.3137600","volume":"19","author":"K Shu","year":"2017","unstructured":"Shu, K., Sliva, A., Wang, S., Tang, J., Liu, H.: Fake news detection on social media: a data mining perspective. SIGKDD Explor. Newsl. 19(1), 22\u201336 (2017). https:\/\/doi.org\/10.1145\/3137597.3137600","journal-title":"SIGKDD Explor. Newsl."},{"issue":"8","key":"13_CR7","doi-asserted-by":"publisher","first-page":"11765","DOI":"10.1007\/s11042-020-10183-2","volume":"80","author":"RK Kaliyar","year":"2021","unstructured":"Kaliyar, R.K., Goswami, A., Narang, P.: FakeBERT: fake news detection in social media with a BERT-based deep learning approach. Multimed. Tools Appl. 80(8), 11765\u201311788 (2021). https:\/\/doi.org\/10.1007\/s11042-020-10183-2","journal-title":"Multimed. Tools Appl."},{"issue":"2","key":"13_CR8","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1109\/MIS.2019.2899143","volume":"34","author":"JCS Reis","year":"2019","unstructured":"Reis, J.C.S., Correia, A., Murai, F., Veloso, A., Benevenuto, F., Cambria, E.: Supervised learning for fake news detection. IEEE Intell. Syst. 34(2), 76\u201381 (2019). https:\/\/doi.org\/10.1109\/MIS.2019.2899143","journal-title":"IEEE Intell. Syst."},{"doi-asserted-by":"publisher","unstructured":"Wang, Y., et al.: EANN: event adversarial neural networks for multi-modal fake news detection. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining, pp. 849\u2013857 (2018). https:\/\/doi.org\/10.1145\/3219819.3219903","key":"13_CR9","DOI":"10.1145\/3219819.3219903"},{"doi-asserted-by":"publisher","unstructured":"Khattar, D., Goud, J.S., Gupta, M., Varma, V.: MVAE: multimodal variational autoencoder for fake news detection. In: The World Wide Web Conference, pp. 2915\u20132921 (2019). https:\/\/doi.org\/10.1145\/3308558.3313552","key":"13_CR10","DOI":"10.1145\/3308558.3313552"},{"doi-asserted-by":"publisher","unstructured":"Giachanou, A., Zhang, G., Rosso, P.: Multimodal multi-image fake news detection. In: 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), pp. 647\u2013654 (2020). https:\/\/doi.org\/10.1109\/DSAA49011.2020.00091","key":"13_CR11","DOI":"10.1109\/DSAA49011.2020.00091"},{"doi-asserted-by":"publisher","unstructured":"Singhal, S., Shah, R.R., Chakraborty, T., Kumaraguru, P., Satoh, S.: SpotFake: a multi-modal framework for fake news detection. In: Proceedings\u20132019 IEEE Fifth International Conference on Multimedia Big Data, BigMM 2019, pp. 39\u201347 (2019). https:\/\/doi.org\/10.1109\/BIGMM.2019.00-44","key":"13_CR12","DOI":"10.1109\/BIGMM.2019.00-44"},{"doi-asserted-by":"crossref","unstructured":"Mangal, D., Sharma, D.K.: A framework for detection and validation of fake news via authorize source matching. In: Micro-Electronics and Telecommunication Engineering, pp. 577\u2013586 (2021)","key":"13_CR13","DOI":"10.1007\/978-981-33-4687-1_54"},{"doi-asserted-by":"publisher","unstructured":"Li, Q., Zhou, W.: Connecting the dots between fact verification and fake news detection (2020). https:\/\/doi.org\/10.48550\/ARXIV.2010.05202","key":"13_CR14","DOI":"10.48550\/ARXIV.2010.05202"},{"doi-asserted-by":"publisher","unstructured":"Shakeel, D., Jain, N.: Fake news detection and fact verification using knowledge graphs and machine learning (2021). https:\/\/doi.org\/10.13140\/RG.2.2.18349.41448","key":"13_CR15","DOI":"10.13140\/RG.2.2.18349.41448"},{"issue":"1","key":"13_CR16","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1177\/1745691620986135","volume":"17","author":"C Batailler","year":"2022","unstructured":"Batailler, C., Brannon, S.M., Teas, P.E., Gawronski, B.: A signal detection approach to understanding the identification of fake news. Perspect. Psychol. Sci. 17(1), 78\u201398 (2022). https:\/\/doi.org\/10.1177\/1745691620986135","journal-title":"Perspect. Psychol. Sci."},{"key":"13_CR17","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1007\/978-3-030-29035-1_22","volume-title":"Advances in Intelligent Networking and Collaborative Systems","author":"MD Ibrishimova","year":"2020","unstructured":"Ibrishimova, M.D., Li, K.F.: A machine learning approach to fake news detection using knowledge verification and natural language processing. In: Barolli, L., Nishino, H., Miwa, H. (eds.) INCoS 2019. AISC, vol. 1035, pp. 223\u2013234. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-29035-1_22"},{"doi-asserted-by":"publisher","unstructured":"Barrios, F., L\u00f3pez, F., Argerich, L., Wachenchauzer, R.: Variations of the similarity function of text rank for automated summarization (2016). https:\/\/doi.org\/10.48550\/arXiv.1602.03606","key":"13_CR18","DOI":"10.48550\/arXiv.1602.03606"},{"key":"13_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"806","DOI":"10.1007\/978-3-319-76941-7_80","volume-title":"Advances in Information Retrieval","author":"R Campos","year":"2018","unstructured":"Campos, R., Mangaravite, V., Pasquali, A., Jorge, A.M., Nunes, C., Jatowt, A.: YAKE! collection-independent automatic keyword extractor. In: Pasi, G., Piwowarski, B., Azzopardi, L., Hanbury, A. (eds.) ECIR 2018. LNCS, vol. 10772, pp. 806\u2013810. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-76941-7_80"},{"issue":"2","key":"13_CR20","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1162\/coli.2010.36.1.36100","volume":"19","author":"MP Marcus","year":"1993","unstructured":"Marcus, M.P., Santorini, B., Marcinkiewicz, M.A.: Building a large annotated corpus of English: the Penn treebank. Comput. Linguist. 19(2), 313\u2013330 (1993). https:\/\/doi.org\/10.1162\/coli.2010.36.1.36100","journal-title":"Comput. Linguist."},{"issue":"4","key":"13_CR21","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1093\/ijl\/3.4.235","volume":"3","author":"GA Miller","year":"1990","unstructured":"Miller, G.A., Beckwith, R., Fellbaum, C., Gross, D., Miller, K.J.: Introduction to wordnet: an on-line lexical database. Int. J. Lexicogr. 3(4), 235\u2013244 (1990). https:\/\/doi.org\/10.1093\/ijl\/3.4.235","journal-title":"Int. J. Lexicogr."},{"doi-asserted-by":"publisher","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space (2013). https:\/\/doi.org\/10.48550\/arXiv.1301.3781","key":"13_CR22","DOI":"10.48550\/arXiv.1301.3781"},{"issue":"1","key":"13_CR23","doi-asserted-by":"publisher","DOI":"10.1002\/SPY2.9","volume":"1","author":"H Ahmed","year":"2018","unstructured":"Ahmed, H., Traore, I., Saad, S.: Detecting opinion spams and fake news using text classification. Secur. Priv. 1(1), e9 (2018). https:\/\/doi.org\/10.1002\/SPY2.9","journal-title":"Secur. Priv."},{"doi-asserted-by":"publisher","unstructured":"Wang, W.Y.: \u2018Liar, Liar Pants on Fire\u2019: a new benchmark dataset for fake news detection,\u201d ACL 2017\u201455th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers), vol. 2, pp. 422\u2013426 (2017). https:\/\/doi.org\/10.18653\/V1\/P17-2067","key":"13_CR24","DOI":"10.18653\/V1\/P17-2067"},{"key":"13_CR25","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"650","DOI":"10.1007\/978-3-030-67664-3_39","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"K Shu","year":"2021","unstructured":"Shu, K., et al.: Early detection of fake news with multi-source weak social supervision. In: Hutter, F., Kersting, K., Lijffijt, J., Valera, I. (eds.) ECML PKDD 2020. LNCS (LNAI), vol. 12459, pp. 650\u2013666. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-67664-3_39"},{"doi-asserted-by":"publisher","unstructured":"Sadeghi, F., Jalaly Bidgoly, A., Amirkhani, H.: FNID: fake news inference dataset (2020). https:\/\/doi.org\/10.21227\/fbzd-sw81","key":"13_CR26","DOI":"10.21227\/fbzd-sw81"},{"doi-asserted-by":"publisher","unstructured":"Liu, H., Lang, B: Machine learning and deep learning methods for intrusion detection systems: a survey. Appl. Sci. 9(20) (2019). https:\/\/doi.org\/10.3390\/app9204396","key":"13_CR27","DOI":"10.3390\/app9204396"},{"issue":"2","key":"13_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5121\/ijdkp.2015.5201","volume":"5","author":"M Hossin","year":"2015","unstructured":"Hossin, M., Sulaiman, M.N.: A review on evaluation metrics for data classification evaluations. Int. J. Data Min. Knowl. Manag. Process 5(2), 1 (2015). https:\/\/doi.org\/10.5121\/ijdkp.2015.5201","journal-title":"Int. J. Data Min. Knowl. Manag. Process"},{"issue":"8","key":"13_CR29","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/NECO.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997). https:\/\/doi.org\/10.1162\/NECO.1997.9.8.1735","journal-title":"Neural Comput."},{"doi-asserted-by":"publisher","unstructured":"Cho, K., et al.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. In: EMNLP 2014\u20132014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference, pp. 1724\u20131734 (2014). https:\/\/doi.org\/10.3115\/v1\/d14-1179","key":"13_CR30","DOI":"10.3115\/v1\/d14-1179"},{"doi-asserted-by":"publisher","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: NAACL HLT 2019\u20142019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies\u2014Proceedings of the Conference, vol. 1, pp. 4171\u20134186 (2018). https:\/\/doi.org\/10.48550\/arxiv.1810.04805","key":"13_CR31","DOI":"10.48550\/arxiv.1810.04805"},{"unstructured":"Snoek, J., Larochelle, H., Adams, R.P.: Practical bayesian optimization of machine learning algorithms. In: Advances in Neural Information Processing Systems, vol. 25 (2012)","key":"13_CR32"}],"container-title":["Lecture Notes in Networks and Systems","Distributed Computing and Artificial Intelligence, 19th International Conference"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-20859-1_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T08:14:57Z","timestamp":1670832897000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20859-1_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,13]]},"ISBN":["9783031208584","9783031208591"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20859-1_13","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2022,12,13]]},"assertion":[{"value":"13 December 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Distributed Computing and Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"L\u00b4Aquila","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 July 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 July 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dcai2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.dcai-conference.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}