{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T19:30:16Z","timestamp":1762543816336,"version":"3.40.3"},"publisher-location":"Cham","reference-count":167,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031314681"},{"type":"electronic","value":"9783031314698"}],"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\/978-3-031-31469-8_2","type":"book-chapter","created":{"date-parts":[[2023,4,27]],"date-time":"2023-04-27T16:01:50Z","timestamp":1682611310000},"page":"17-40","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Misinformation and\u00a0Disinformation on\u00a0Social Media: An Updated Survey of\u00a0Challenges and\u00a0Current Trends"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9092-8918","authenticated-orcid":false,"given":"Fabrizio","family":"Lo Scudo","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,28]]},"reference":[{"key":"2_CR1","doi-asserted-by":"crossref","unstructured":"Ahmadi, N., Lee, J., Papotti, P., Saeed, M.: Explainable fact checking with probabilistic answer set programming. arXiv preprint arXiv:1906.09198 (2019)","DOI":"10.36370\/tto.2019.15"},{"key":"2_CR2","doi-asserted-by":"crossref","unstructured":"Aker, A., Derczynski, L., Bontcheva, K.: Simple open stance classification for rumour analysis. arXiv preprint arXiv:1708.05286 (2017)","DOI":"10.26615\/978-954-452-049-6_005"},{"key":"2_CR3","doi-asserted-by":"crossref","unstructured":"Alhindi, T., Petridis, S., Muresan, S.: Where is your evidence: improving fact-checking by justification modeling. In: Proceedings of the first workshop on fact extraction and verification (FEVER), pp. 85\u201390 (2018)","DOI":"10.18653\/v1\/W18-5513"},{"key":"2_CR4","doi-asserted-by":"publisher","unstructured":"Alhindi, T., Petridis, S., Muresan, S.: Where is your evidence: improving fact-checking by justification modeling. In: Proceedings of the First Workshop on Fact Extraction and VERification (FEVER), pp. 85\u201390. Association for Computational Linguistics, Brussels, Belgium (2018). https:\/\/doi.org\/10.18653\/v1\/W18-5513, https:\/\/www.aclweb.org\/anthology\/W18-5513","DOI":"10.18653\/v1\/W18-5513"},{"issue":"2","key":"2_CR5","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.: Social media and fake news in the 2016 election. J. Econ. Perspect. 31(2), 211\u201336 (2017)","journal-title":"J. Econ. Perspect."},{"key":"2_CR6","doi-asserted-by":"crossref","unstructured":"Aly, R., et al.: FEVEROUS: fact extraction and verification over unstructured and structured information. In: 35th Conference on Neural Information Processing Systems (NeurIPS 2021) Track on Datasets and Benchmarks (2021)","DOI":"10.18653\/v1\/2021.fever-1.1"},{"key":"2_CR7","unstructured":"Argamon-Engelson, S., Koppel, M., Avneri, G.: Style-based text categorization: what newspaper am i reading. In: Proceedings of the AAAI Workshop on Text Categorization, pp. 1\u20134 (1998)"},{"issue":"6","key":"2_CR8","doi-asserted-by":"publisher","first-page":"939","DOI":"10.14778\/3380750.3380762","volume":"13","author":"A Asudeh","year":"2020","unstructured":"Asudeh, A., Jagadish, H.V., Wu, Y., Yu, C.: On detecting cherry-picked trendlines. Proc. VLDB Endow. 13(6), 939\u2013952 (2020)","journal-title":"Proc. VLDB Endow."},{"key":"2_CR9","doi-asserted-by":"crossref","unstructured":"Atanasova, P., Simonsen, J.G., Lioma, C., Augenstein, I.: Generating fact checking explanations. arXiv preprint arXiv:2004.05773 (2020)","DOI":"10.18653\/v1\/2020.acl-main.656"},{"key":"2_CR10","doi-asserted-by":"publisher","unstructured":"Augenstein, I., et al.: MultiFC: a real-world multi-domain dataset for evidence-based fact checking of claims. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 4685\u20134697. Association for Computational Linguistics, Hong Kong, China (2019). https:\/\/doi.org\/10.18653\/v1\/D19-1475, https:\/\/www.aclweb.org\/anthology\/D19-1475","DOI":"10.18653\/v1\/D19-1475"},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"Augenstein, I., et al.: MultiFC: a real-world multi-domain dataset for evidence-based fact checking of claims. arXiv preprint arXiv:1909.03242 (2019)","DOI":"10.18653\/v1\/D19-1475"},{"issue":"16","key":"2_CR12","doi-asserted-by":"crossref","first-page":"2312","DOI":"10.1080\/1461670X.2019.1593881","volume":"20","author":"A Barnoy","year":"2019","unstructured":"Barnoy, A., Reich, Z.: The when, why, how and so-what of verifications. Journal. Stud. 20(16), 2312\u20132330 (2019)","journal-title":"Journal. Stud."},{"key":"2_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1007\/978-3-030-58219-7_17","volume-title":"Experimental IR Meets Multilinguality, Multimodality, and Interaction","author":"A Barr\u00f3n-Cede\u00f1o","year":"2020","unstructured":"Barr\u00f3n-Cede\u00f1o, A., et al.: Overview of CheckThat! 2020: automatic identification and verification of claims in social media. In: Arampatzis, A., et al. (eds.) CLEF 2020. LNCS, vol. 12260, pp. 215\u2013236. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58219-7_17"},{"key":"2_CR14","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780190923624.001.0001","volume-title":"Network Propaganda: Manipulation, Disinformation, and Radicalization in American Politics","author":"Y Benkler","year":"2018","unstructured":"Benkler, Y., Faris, R., Roberts, H.: Network Propaganda: Manipulation, Disinformation, and Radicalization in American Politics. Oxford University Press, Oxford (2018)"},{"key":"2_CR15","doi-asserted-by":"crossref","unstructured":"Bo, H., McConville, R., Hong, J., Liu, W.: Ego-graph replay based continual learning for misinformation engagement prediction. arXiv preprint arXiv:2207.12105 (2022)","DOI":"10.1109\/IJCNN55064.2022.9892557"},{"issue":"1","key":"2_CR16","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1007\/s13735-017-0143-x","volume":"7","author":"C Boididou","year":"2018","unstructured":"Boididou, C., Papadopoulos, S., Zampoglou, M., Apostolidis, L., Papadopoulou, O., Kompatsiaris, Y.: Detection and visualization of misleading content on twitter. Int. J. Multimed. Inf. Retr. 7(1), 71\u201386 (2018)","journal-title":"Int. J. Multimed. Inf. Retr."},{"issue":"4","key":"2_CR17","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1080\/08900520701583586","volume":"22","author":"SL Borden","year":"2007","unstructured":"Borden, S.L., Tew, C.: The role of journalist and the performance of journalism: ethical lessons from \u201cfake\u2019\u2019 news (seriously). J. Mass Media Ethics 22(4), 300\u2013314 (2007)","journal-title":"J. Mass Media Ethics"},{"key":"2_CR18","doi-asserted-by":"publisher","DOI":"10.7208\/chicago\/9780226291093.001.0001","volume-title":"The Chicago Guide to Fact-Checking","author":"B Borel","year":"2016","unstructured":"Borel, B.: The Chicago Guide to Fact-Checking. University of Chicago Press, Chicago (2016)"},{"key":"2_CR19","doi-asserted-by":"crossref","unstructured":"Bowman, S.R., Angeli, G., Potts, C., Manning, C.D.: A large annotated corpus for learning natural language inference. arXiv preprint arXiv:1508.05326 (2015)","DOI":"10.18653\/v1\/D15-1075"},{"issue":"28","key":"2_CR20","doi-asserted-by":"publisher","first-page":"7313","DOI":"10.1073\/pnas.1618923114","volume":"114","author":"WJ Brady","year":"2017","unstructured":"Brady, W.J., Wills, J.A., Jost, J.T., Tucker, J.A., Van Bavel, J.J.: Emotion shapes the diffusion of moralized content in social networks. Proc. Natl. Acad. Sci. 114(28), 7313\u20137318 (2017)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"2_CR21","doi-asserted-by":"crossref","unstructured":"Chen, M., Chu, X., Subbalakshmi, K.: MMCoVaR: multimodal COVID-19 vaccine focused data repository for fake news detection and a baseline architecture for classification. In: Proceedings of the 2021 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 31\u201338 (2021)","DOI":"10.1145\/3487351.3488346"},{"key":"2_CR22","unstructured":"Chen, W., et al.: TabFact: a large-scale dataset for table-based fact verification. In: 8th International Conference on Learning Representations, ICLR 2020. Addis Ababa, Ethiopia (2020). https:\/\/openreview.net\/forum?id=rkeJRhNYDH"},{"issue":"6","key":"2_CR23","doi-asserted-by":"publisher","first-page":"e0128193","DOI":"10.1371\/journal.pone.0128193","volume":"10","author":"GL Ciampaglia","year":"2015","unstructured":"Ciampaglia, G.L., Shiralkar, P., Rocha, L.M., Bollen, J., Menczer, F., Flammini, A.: Computational fact checking from knowledge networks. PLoS ONE 10(6), e0128193 (2015)","journal-title":"PLoS ONE"},{"key":"2_CR24","doi-asserted-by":"crossref","unstructured":"Conneau, A., Kiela, D., Schwenk, H., Barrault, L., Bordes, A.: Supervised learning of universal sentence representations from natural language inference data. arXiv preprint arXiv:1705.02364 (2017)","DOI":"10.18653\/v1\/D17-1070"},{"key":"2_CR25","unstructured":"Cui, L., Lee, D.: CoAID: COVID-19 healthcare misinformation dataset. arXiv preprint arXiv:2006.00885 (2020)"},{"key":"2_CR26","doi-asserted-by":"crossref","unstructured":"Cui, L., Seo, H., Tabar, M., Ma, F., Wang, S., Lee, D.: DETERRENT: knowledge guided graph attention network for detecting healthcare misinformation. In: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 492\u2013502 (2020)","DOI":"10.1145\/3394486.3403092"},{"key":"2_CR27","doi-asserted-by":"crossref","unstructured":"Derczynski, L., et al.: SemEVAL-2017 task 8: RumourEVAL: determining rumour veracity and support for rumours. arXiv preprint arXiv:1704.05972 (2017)","DOI":"10.18653\/v1\/S17-2006"},{"key":"2_CR28","unstructured":"Diggelmann, T., Boyd-Graber, J.L., Bulian, J., Ciaramita, M., Leippold, M.: CLIMATE-FEVER: a dataset for verification of real-world climate claims. CoRR abs\/2012.00614 (2020). https:\/\/arxiv.org\/abs\/2012.00614"},{"key":"2_CR29","doi-asserted-by":"crossref","unstructured":"Enayet, O., El-Beltagy, S.R.: NileTMRG at SemEVAL-2017 task 8: determining rumour and veracity support for rumours on Twitter. In: Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pp. 470\u2013474 (2017)","DOI":"10.18653\/v1\/S17-2082"},{"key":"2_CR30","doi-asserted-by":"crossref","unstructured":"Fan, A., et al.: Generating fact checking briefs. arXiv preprint arXiv:2011.05448 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.580"},{"key":"2_CR31","doi-asserted-by":"crossref","unstructured":"Fazio, L.: Pausing to consider why a headline is true or false can help reduce the sharing of false news. Harvard Kennedy School Misinformation Review 1(2) (2020)","DOI":"10.37016\/mr-2020-009"},{"issue":"2","key":"2_CR32","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1080\/17512786.2011.616655","volume":"6","author":"T Flew","year":"2012","unstructured":"Flew, T., Spurgeon, C., Daniel, A., Swift, A.: The promise of computational journalism. Journal. Pract. 6(2), 157\u2013171 (2012)","journal-title":"Journal. Pract."},{"issue":"509","key":"2_CR33","doi-asserted-by":"publisher","first-page":"315","DOI":"10.5406\/jamerfolk.128.509.0315","volume":"128","author":"R Frank","year":"2015","unstructured":"Frank, R.: Caveat lector: fake news as folklore. J. Am. Folk. 128(509), 315\u2013332 (2015)","journal-title":"J. Am. Folk."},{"key":"2_CR34","doi-asserted-by":"crossref","unstructured":"Gad-Elrab, M.H., Stepanova, D., Urbani, J., Weikum, G.: ExFaKT: a framework for explaining facts over knowledge graphs and text. In: Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, pp. 87\u201395 (2019)","DOI":"10.1145\/3289600.3290996"},{"key":"2_CR35","doi-asserted-by":"crossref","unstructured":"Gallo, I., Ria, G., Landro, N., La Grassa, R.: Image and text fusion for UPMC food-101 using BERT and CNNs. In: 2020 35th International Conference on Image and Vision Computing New Zealand (IVCNZ), pp. 1\u20136. IEEE (2020)","DOI":"10.1109\/IVCNZ51579.2020.9290622"},{"key":"2_CR36","doi-asserted-by":"crossref","unstructured":"Gencheva, P., Nakov, P., M\u00e0rquez, L., Barr\u00f3n-Cede\u00f1o, A., Koychev, I.: A context-aware approach for detecting worth-checking claims in political debates. In: 2017 Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP, pp. 267\u2013276 (2017)","DOI":"10.26615\/978-954-452-049-6_037"},{"issue":"2","key":"2_CR37","doi-asserted-by":"publisher","first-page":"551","DOI":"10.25300\/MISQ\/2018\/13215","volume":"42","author":"JF George","year":"2018","unstructured":"George, J.F., Gupta, M., Giordano, G., Mills, A.M., Tennant, V.M., Lewis, C.C.: The effects of communication media and culture on deception detection accuracy. MIS Q. 42(2), 551\u2013575 (2018)","journal-title":"MIS Q."},{"key":"2_CR38","unstructured":"Graves, D.: Understanding the promise and limits of automated fact-checking (2018)"},{"key":"2_CR39","doi-asserted-by":"crossref","unstructured":"Guo, H., Cao, J., Zhang, Y., Guo, J., Li, J.: Rumor detection with hierarchical social attention network. In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management, pp. 943\u2013951 (2018)","DOI":"10.1145\/3269206.3271709"},{"key":"2_CR40","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1162\/tacl_a_00454","volume":"10","author":"Z Guo","year":"2022","unstructured":"Guo, Z., Schlichtkrull, M., Vlachos, A.: A survey on automated fact-checking. Trans. Assoc. Comput. Linguist. 10, 178\u2013206 (2022)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"2_CR41","doi-asserted-by":"crossref","unstructured":"Gupta, A., Srikumar, V.: X-fact: A new benchmark dataset for multilingual fact checking. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pp. 675\u2013682 (2021)","DOI":"10.18653\/v1\/2021.acl-short.86"},{"key":"2_CR42","doi-asserted-by":"publisher","unstructured":"Gupta, V., Mehta, M., Nokhiz, P., Srikumar, V.: INFOTABS: inference on tables as semi-structured data. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 2309\u20132324. Association for Computational Linguistics (2020). https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.210, https:\/\/www.aclweb.org\/anthology\/2020.acl-main.210","DOI":"10.18653\/v1\/2020.acl-main.210"},{"key":"2_CR43","doi-asserted-by":"crossref","unstructured":"Gururangan, S., Swayamdipta, S., Levy, O., Schwartz, R., Bowman, S.R., Smith, N.A.: Annotation artifacts in natural language inference data. arXiv preprint arXiv:1803.02324 (2018)","DOI":"10.18653\/v1\/N18-2017"},{"key":"2_CR44","doi-asserted-by":"publisher","unstructured":"Hanselowski, A., Stab, C., Schulz, C., Li, Z., Gurevych, I.: A richly annotated corpus for different tasks in automated fact-checking. In: Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), pp. 493\u2013503. Association for Computational Linguistics, Hong Kong, China (2019). https:\/\/doi.org\/10.18653\/v1\/K19-1046, https:\/\/www.aclweb.org\/anthology\/K19-1046","DOI":"10.18653\/v1\/K19-1046"},{"key":"2_CR45","unstructured":"Hassan, N., et al.: The quest to automate fact-checking. In: Proceedings of the 2015 Computation+ Journalism Symposium (2015)"},{"key":"2_CR46","doi-asserted-by":"crossref","unstructured":"Hassan, N., Li, C., Tremayne, M.: Detecting check-worthy factual claims in presidential debates. In: Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, pp. 1835\u20131838 (2015)","DOI":"10.1145\/2806416.2806652"},{"issue":"12","key":"2_CR47","doi-asserted-by":"publisher","first-page":"1945","DOI":"10.14778\/3137765.3137815","volume":"10","author":"N Hassan","year":"2017","unstructured":"Hassan, N., et al.: ClaimBuster: the first-ever end-to-end fact-checking system. Proc. VLDB Endow. 10(12), 1945\u20131948 (2017)","journal-title":"Proc. VLDB Endow."},{"key":"2_CR48","doi-asserted-by":"publisher","first-page":"896","DOI":"10.1287\/mksc.2022.1353","volume":"41","author":"S He","year":"2022","unstructured":"He, S., Hollenbeck, B., Proserpio, D.: The market for fake reviews. Mark. Sci. 41, 896\u2013921 (2022)","journal-title":"Mark. Sci."},{"key":"2_CR49","unstructured":"Hermann, K.M., et al.: Teaching machines to read and comprehend. In: Advances in Neural Information Processing Systems, vol. 28 (2015)"},{"key":"2_CR50","doi-asserted-by":"crossref","unstructured":"Horne, B.D., Adali, S., Sikdar, S.: Identifying the social signals that drive online discussions: a case study of reddit communities. In: 2017 26th International Conference on Computer Communication and Networks (ICCCN), pp. 1\u20139. IEEE (2017)","DOI":"10.1109\/ICCCN.2017.8038388"},{"key":"2_CR51","doi-asserted-by":"crossref","unstructured":"Horne, B.D., Dron, W., Khedr, S., Adali, S.: Assessing the news landscape: a multi-module toolkit for evaluating the credibility of news. In: 2018 Companion Proceedings of the The Web Conference, pp. 235\u2013238 (2018)","DOI":"10.1145\/3184558.3186987"},{"key":"2_CR52","unstructured":"Horne, B.D., Khedr, S., Adali, S.: Sampling the news producers: a large news and feature data set for the study of the complex media landscape. In: Proceedings of the Twelfth International Conference on Web and Social Media, ICWSM 2018, Stanford, California, USA, 25-28 June 2018, pp. 518\u2013527. AAAI Press (2018). https:\/\/aaai.org\/ocs\/index.php\/ICWSM\/ICWSM18\/paper\/view\/17796"},{"key":"2_CR53","doi-asserted-by":"crossref","unstructured":"Horne, B.D., Nevo, D., O\u2019Donovan, J., Cho, J.H., Adal\u0131, S.: Rating reliability and bias in news articles: does AI assistance help everyone?. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 13, pp. 247\u2013256 (2019)","DOI":"10.1609\/icwsm.v13i01.3226"},{"issue":"22","key":"2_CR54","first-page":"1094","volume":"3","author":"C Jack","year":"2017","unstructured":"Jack, C.: Lexicon of lies: terms for problematic information. Data Soc. 3(22), 1094\u20131096 (2017)","journal-title":"Data Soc."},{"key":"2_CR55","unstructured":"Jain, S., Wallace, B.C.: Attention is not explanation. arXiv preprint arXiv:1902.10186 (2019)"},{"key":"2_CR56","doi-asserted-by":"publisher","unstructured":"Jiang, Y., Bordia, S., Zhong, Z., Dognin, C., Singh, M., Bansal, M.: HoVer: a dataset for many-hop fact extraction and claim verification. In: Findings of the Association for Computational Linguistics: EMNLP 2020, pp. 3441\u20133460. Association for Computational Linguistics (2020). https:\/\/doi.org\/10.18653\/v1\/2020.findings-emnlp.309, https:\/\/www.aclweb.org\/anthology\/2020.findings-emnlp.309","DOI":"10.18653\/v1\/2020.findings-emnlp.309"},{"key":"2_CR57","unstructured":"Jindal, S., Sood, R., Singh, R., Vatsa, M., Chakraborty, T.: NewsBag: a multimodal benchmark dataset for fake news detection. In: CEUR Workshop Proceedings, vol. 2560, pp. 138\u2013145 (2020)"},{"issue":"3","key":"2_CR58","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1109\/TBDATA.2019.2921572","volume":"7","author":"J Johnson","year":"2019","unstructured":"Johnson, J., Douze, M., J\u00e9gou, H.: Billion-scale similarity search with GPUs. IEEE Trans. Big Data 7(3), 535\u2013547 (2019)","journal-title":"IEEE Trans. Big Data"},{"key":"2_CR59","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1017\/S1930297500005271","volume":"8","author":"DM Kahan","year":"2012","unstructured":"Kahan, D.M.: Ideology, motivated reasoning, and cognitive reflection: an experimental study. Judgm. Decis. Mak. 8, 407\u201324 (2012)","journal-title":"Judgm. Decis. Mak."},{"key":"2_CR60","doi-asserted-by":"crossref","unstructured":"Kim, J., Tabibian, B., Oh, A., Sch\u00f6lkopf, B., Gomez-Rodriguez, M.: Leveraging the crowd to detect and reduce the spread of fake news and misinformation. In: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, pp. 324\u2013332 (2018)","DOI":"10.1145\/3159652.3159734"},{"issue":"2","key":"2_CR61","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3412869","volume":"2","author":"L Konstantinovskiy","year":"2021","unstructured":"Konstantinovskiy, L., Price, O., Babakar, M., Zubiaga, A.: Toward automated factchecking: developing an annotation schema and benchmark for consistent automated claim detection. Digit. threats: Res. Pract. 2(2), 1\u201316 (2021)","journal-title":"Digit. threats: Res. Pract."},{"key":"2_CR62","doi-asserted-by":"crossref","unstructured":"Kotonya, N., Toni, F.: Explainable automated fact-checking: a survey. arXiv preprint arXiv:2011.03870 (2020)","DOI":"10.18653\/v1\/2020.coling-main.474"},{"key":"2_CR63","doi-asserted-by":"publisher","first-page":"115412","DOI":"10.1016\/j.eswa.2021.115412","volume":"184","author":"R Kumari","year":"2021","unstructured":"Kumari, R., Ekbal, A.: AMFB: attention based multimodal factorized bilinear pooling for multimodal fake news detection. Expert Syst. Appl. 184, 115412 (2021)","journal-title":"Expert Syst. Appl."},{"key":"2_CR64","doi-asserted-by":"crossref","unstructured":"Lee, N., Bang, Y., Madotto, A., Khabsa, M., Fung, P.: Towards few-shot fact-checking via perplexity. arXiv preprint arXiv:2103.09535 (2021)","DOI":"10.18653\/v1\/2021.naacl-main.158"},{"key":"2_CR65","doi-asserted-by":"crossref","unstructured":"Lee, N., Li, B.Z., Wang, S., Yih, W.t., Ma, H., Khabsa, M.: Language models as fact checkers? arXiv preprint arXiv:2006.04102 (2020)","DOI":"10.18653\/v1\/2020.fever-1.5"},{"issue":"4","key":"2_CR66","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1016\/j.jarmac.2017.07.008","volume":"6","author":"S Lewandowsky","year":"2017","unstructured":"Lewandowsky, S., Ecker, U.K., Cook, J.: Beyond misinformation: understanding and coping with the \u201cpost-truth\u2019\u2019 era. J. Appl. Res. Mem. Cogn. 6(4), 353\u2013369 (2017)","journal-title":"J. Appl. Res. Mem. Cogn."},{"key":"2_CR67","unstructured":"Lewis, P., et al.: Retrieval-augmented generation for knowledge-intensive NLP tasks. In: Advanced in Neural Information Processing System, vol. 33, pp. 9459\u20139474 (2020)"},{"issue":"2","key":"2_CR68","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2897350.2897352","volume":"17","author":"Y Li","year":"2016","unstructured":"Li, Y., et al.: A survey on truth discovery. ACM SIGKDD Explor. Newsl. 17(2), 1\u201316 (2016)","journal-title":"ACM SIGKDD Explor. Newsl."},{"key":"2_CR69","doi-asserted-by":"crossref","unstructured":"Li, Y., Jiang, B., Shu, K., Liu, H.: MM-COVID: a multilingual and multimodal data repository for combating COVID-19 disinformation. arXiv preprint arXiv:2011.04088 (2020)","DOI":"10.1109\/BigData50022.2020.9378472"},{"key":"2_CR70","doi-asserted-by":"crossref","unstructured":"Lu, Y.J., Li, C.T.: GCAN: graph-aware co-attention networks for explainable fake news detection on social media. arXiv preprint arXiv:2004.11648 (2020)","DOI":"10.18653\/v1\/2020.acl-main.48"},{"key":"2_CR71","doi-asserted-by":"crossref","unstructured":"Luken, J., Jiang, N., de Marneffe, M.C.: QED: a fact verification system for the fever shared task. In: Proceedings of the First Workshop on Fact Extraction and VERification (FEVER), pp. 156\u2013160 (2018)","DOI":"10.18653\/v1\/W18-5526"},{"key":"2_CR72","unstructured":"Ma, J., et al.: Detecting rumors from microblogs with recurrent neural networks. In: Kambhampati, S. (ed.) Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9\u201315 July 2016, pp. 3818\u20133824. IJCAI\/AAAI Press (2016). http:\/\/www.ijcai.org\/Abstract\/16\/537"},{"key":"2_CR73","unstructured":"Mahabadi, R.K., Belinkov, Y., Henderson, J.: End-to-end bias mitigation by modelling biases in corpora. arXiv preprint arXiv:1909.06321 (2019)"},{"issue":"2","key":"2_CR74","doi-asserted-by":"publisher","first-page":"230","DOI":"10.17705\/1thci.00168","volume":"14","author":"L Manikonda","year":"2022","unstructured":"Manikonda, L., Nevo, D., Horne, B.D., Arrington, C., Adali, S.: The reasoning behind fake news assessments: a linguistic analysis. AIS Trans. Human-Comput. Interact. 14(2), 230\u2013253 (2022)","journal-title":"AIS Trans. Human-Comput. Interact."},{"key":"2_CR75","doi-asserted-by":"publisher","unstructured":"Maynez, J., Narayan, S., Bohnet, B., McDonald, R.: On faithfulness and factuality in abstractive summarization. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 1906\u20131919. Association for Computational Linguistics (2020). https:\/\/doi.org\/10.18653\/v1\/2020.acl-main.173, https:\/\/aclanthology.org\/2020.acl-main.173","DOI":"10.18653\/v1\/2020.acl-main.173"},{"key":"2_CR76","doi-asserted-by":"crossref","unstructured":"McCoy, R.T., Pavlick, E., Linzen, T.: Right for the wrong reasons: diagnosing syntactic heuristics in natural language inference. arXiv preprint arXiv:1902.01007 (2019)","DOI":"10.18653\/v1\/P19-1334"},{"issue":"4","key":"2_CR77","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1177\/0002764217701217","volume":"61","author":"P Mihailidis","year":"2017","unstructured":"Mihailidis, P., Viotty, S.: Spreadable spectacle in digital culture: civic expression, fake news, and the role of media literacies in \u201cpost-fact\u2019\u2019 society. Am. Behav. Sci. 61(4), 441\u2013454 (2017)","journal-title":"Am. Behav. Sci."},{"key":"2_CR78","doi-asserted-by":"publisher","unstructured":"Mihaylova, T., Karadzhov, G., Atanasova, P., Baly, R., Mohtarami, M., Nakov, P.: SemEval-2019 task 8: Fact checking in community question answering forums. In: Proceedings of the 13th International Workshop on Semantic Evaluation, pp. 860\u2013869. Association for Computational Linguistics, Minneapolis, Minnesota, USA (2019). https:\/\/doi.org\/10.18653\/v1\/S19-2149, https:\/\/www.aclweb.org\/anthology\/S19-2149","DOI":"10.18653\/v1\/S19-2149"},{"key":"2_CR79","unstructured":"Mitra, T., Gilbert, E.: CREDBANK: A large-scale social media corpus with associated credibility annotations. In: Cha, M., Mascolo, C., Sandvig, C. (eds.) Proceedings of the Ninth International Conference on Web and Social Media, ICWSM 2015, University of Oxford, Oxford, UK, 26\u201329 May 2015, pp. 258\u2013267. AAAI Press (2015). http:\/\/www.aaai.org\/ocs\/index.php\/ICWSM\/ICWSM15\/paper\/view\/10582"},{"issue":"2","key":"2_CR80","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1177\/0002764219878224","volume":"65","author":"MD Molina","year":"2021","unstructured":"Molina, M.D., Sundar, S.S., Le, T., Lee, D.: \u201cfake news\u2019\u2019 is not simply false information: a concept explication and taxonomy of online content. Am. Behav. Sci. 65(2), 180\u2013212 (2021)","journal-title":"Am. Behav. Sci."},{"key":"2_CR81","unstructured":"Monti, F., Frasca, F., Eynard, D., Mannion, D., Bronstein, M.M.: Fake news detection on social media using geometric deep learning. arXiv preprint arXiv:1902.06673 (2019)"},{"key":"2_CR82","doi-asserted-by":"crossref","unstructured":"Moravec, P., Minas, R., Dennis, A.R.: Fake news on social media: people believe what they want to believe when it makes no sense at all. Kelley School of Business research paper (18\u201387) (2018)","DOI":"10.2139\/ssrn.3269541"},{"key":"2_CR83","unstructured":"Nakamura, K., Levy, S., Wang, W.Y.: r\/Fakeddit: a new multimodal benchmark dataset for fine-grained fake news detection. arXiv preprint arXiv:1911.03854 (2019)"},{"key":"2_CR84","doi-asserted-by":"crossref","unstructured":"Nakashole, N., Mitchell, T.: Language-aware truth assessment of fact candidates. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 1009\u20131019 (2014)","DOI":"10.3115\/v1\/P14-1095"},{"key":"2_CR85","doi-asserted-by":"crossref","unstructured":"Nakov, P., et al.: Automated fact-checking for assisting human fact-checkers. arXiv preprint arXiv:2103.07769 (2021)","DOI":"10.24963\/ijcai.2021\/619"},{"key":"2_CR86","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1007\/978-3-030-72240-1_75","volume-title":"Advances in Information Retrieval","author":"P Nakov","year":"2021","unstructured":"Nakov, P., et al.: The CLEF-2021 CheckThat! lab on detecting check-worthy claims, previously fact-checked claims, and fake news. In: Hiemstra, D., Moens, M.-F., Mothe, J., Perego, R., Potthast, M., Sebastiani, F. (eds.) ECIR 2021. LNCS, vol. 12657, pp. 639\u2013649. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-72240-1_75"},{"key":"2_CR87","doi-asserted-by":"crossref","unstructured":"Borges do Nascimento, I.J., et al.: Infodemics and health misinformation: a systematic review of reviews. Bull. World Health Org. 100(9), 544\u2013561 (2022)","DOI":"10.2471\/BLT.21.287654"},{"issue":"2","key":"2_CR88","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1037\/1089-2680.2.2.175","volume":"2","author":"RS Nickerson","year":"1998","unstructured":"Nickerson, R.S.: Confirmation bias: a ubiquitous phenomenon in many guises. Rev. Gen. Psychol. 2(2), 175\u2013220 (1998)","journal-title":"Rev. Gen. Psychol."},{"key":"2_CR89","doi-asserted-by":"crossref","unstructured":"Nie, Y., Chen, H., Bansal, M.: Combining fact extraction and verification with neural semantic matching networks. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 6859\u20136866 (2019)","DOI":"10.1609\/aaai.v33i01.33016859"},{"key":"2_CR90","doi-asserted-by":"crossref","unstructured":"Nielsen, D.S., McConville, R.: MuMiN: a large-scale multilingual multimodal fact-checked misinformation social network dataset. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 3141\u20133153 (2022)","DOI":"10.1145\/3477495.3531744"},{"key":"2_CR91","doi-asserted-by":"publisher","unstructured":"Olan, F., Jayawickrama, U., Arakpogun, E.O., Suklan, J., Liu, S.: Fake news on social media: the impact on society. Inf. Syst. Front., 1\u201316 (2022). https:\/\/doi.org\/10.1007\/s10796-022-10242-z","DOI":"10.1007\/s10796-022-10242-z"},{"key":"2_CR92","volume-title":"What is Web 2.0","author":"T O\u2019reilly","year":"2009","unstructured":"O\u2019reilly, T.: What is Web 2.0. \u201cO\u2019Reilly Media Inc\u2019\u2019, Sebastopol (2009)"},{"key":"2_CR93","unstructured":"Passaro, L.C., Bondielli, A., Lenci, A., Marcelloni, F.: UNIPI-NLE at CheckThat! 2020: approaching fact checking from a sentence similarity perspective through the lens of transformers. In: CLEF (Working Notes) (2020)"},{"key":"2_CR94","doi-asserted-by":"crossref","unstructured":"Pennycook, G., Rand, D.G.: Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. Cognition 188(-), 39\u201350 (2019)","DOI":"10.1016\/j.cognition.2018.06.011"},{"issue":"5","key":"2_CR95","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, D.G.: The psychology of fake news. Trends Cogn. Sci. 25(5), 388\u2013402 (2021)","journal-title":"Trends Cogn. Sci."},{"key":"2_CR96","doi-asserted-by":"crossref","unstructured":"Popat, K., Mukherjee, S., Str\u00f6tgen, J., Weikum, G.: Credibility assessment of textual claims on the web. In: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, pp. 2173\u20132178 (2016)","DOI":"10.1145\/2983323.2983661"},{"key":"2_CR97","doi-asserted-by":"publisher","unstructured":"Popat, K., Mukherjee, S., Str\u00f6tgen, J., Weikum, G.: Credibility assessment of textual claims on the web. In: Mukhopadhyay, S., et al. (eds.) Proceedings of the 25th ACM International Conference on Information and Knowledge Management, CIKM 2016, Indianapolis, IN, USA, 24\u201328 Oct 2016, pp. 2173\u20132178. ACM (2016). https:\/\/doi.org\/10.1145\/2983323.2983661","DOI":"10.1145\/2983323.2983661"},{"key":"2_CR98","doi-asserted-by":"crossref","unstructured":"Potthast, M., Kiesel, J., Reinartz, K., Bevendorff, J., Stein, B.: A stylometric inquiry into hyperpartisan and fake news. arXiv preprint arXiv:1702.05638 (2017)","DOI":"10.18653\/v1\/P18-1022"},{"key":"2_CR99","doi-asserted-by":"publisher","unstructured":"Potthast, M., Kiesel, J., Reinartz, K., Bevendorff, J., Stein, B.: A stylometric inquiry into hyperpartisan and fake news. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 231\u2013240. Association for Computational Linguistics, Melbourne, Australia (2018). https:\/\/doi.org\/10.18653\/v1\/P18-1022, https:\/\/www.aclweb.org\/anthology\/P18-1022","DOI":"10.18653\/v1\/P18-1022"},{"key":"2_CR100","doi-asserted-by":"crossref","unstructured":"Pruthi, D., Gupta, M., Dhingra, B., Neubig, G., Lipton, Z.C.: Learning to deceive with attention-based explanations. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 4782\u20134793 (2020)","DOI":"10.18653\/v1\/2020.acl-main.432"},{"key":"2_CR101","doi-asserted-by":"crossref","unstructured":"Qian, S., Wang, J., Hu, J., Fang, Q., Xu, C.: Hierarchical multi-modal contextual attention network for fake news detection. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 153\u2013162 (2021)","DOI":"10.1145\/3404835.3462871"},{"key":"2_CR102","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.neunet.2021.11.006","volume":"146","author":"C Raj","year":"2022","unstructured":"Raj, C., Meel, P.: ARCNN framework for multimodal infodemic detection. Neural Netw. 146, 36\u201368 (2022)","journal-title":"Neural Netw."},{"key":"2_CR103","doi-asserted-by":"crossref","unstructured":"Rashkin, H., Choi, E., Jang, J.Y., Volkova, S., Choi, Y.: Truth of varying shades: analyzing language in fake news and political fact-checking. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 2931\u20132937 (2017)","DOI":"10.18653\/v1\/D17-1317"},{"key":"2_CR104","doi-asserted-by":"publisher","unstructured":"Rashkin, H., Choi, E., Jang, J.Y., Volkova, S., Choi, Y.: Truth of varying shades: analyzing language in fake news and political fact-checking. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 2931\u20132937. Association for Computational Linguistics, Copenhagen, Denmark (2017). https:\/\/doi.org\/10.18653\/v1\/D17-1317, https:\/\/www.aclweb.org\/anthology\/D17-1317","DOI":"10.18653\/v1\/D17-1317"},{"key":"2_CR105","doi-asserted-by":"publisher","unstructured":"Redi, M., Fetahu, B., Morgan, J.T., Taraborelli, D.: Citation needed: a taxonomy and algorithmic assessment of Wikipedia\u2019s verifiability. In: Liu, L., et al. (eds.) The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, 13\u201317 May 2019, pp. 1567\u20131578. ACM (2019). https:\/\/doi.org\/10.1145\/3308558.3313618","DOI":"10.1145\/3308558.3313618"},{"key":"2_CR106","doi-asserted-by":"crossref","unstructured":"Rezayi, S., Soleymani, S., Arabnia, H.R., Li, S.: Socially aware multimodal deep neural networks for fake news classification. In: 2021 IEEE 4th International Conference on Multimedia Information Processing and Retrieval (MIPR), pp. 253\u2013259. IEEE (2021)","DOI":"10.1109\/MIPR51284.2021.00048"},{"key":"2_CR107","doi-asserted-by":"crossref","unstructured":"Rubin, V.L.: Disinformation and misinformation triangle: a conceptual model for \u201cfake news\u201d epidemic, causal factors and interventions. J. Documentation 75, 1013\u20131034 (2019)","DOI":"10.1108\/JD-12-2018-0209"},{"key":"2_CR108","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-95656-1","volume-title":"Misinformation and Disinformation: Detecting Fakes with the Eye and AI","author":"VL Rubin","year":"2022","unstructured":"Rubin, V.L.: Misinformation and Disinformation: Detecting Fakes with the Eye and AI. Springer Nature, Berlin (2022)"},{"key":"2_CR109","doi-asserted-by":"publisher","unstructured":"Saakyan, A., Chakrabarty, T., Muresan, S.: COVID-Fact: Fact extraction and verification of real-world claims on COVID-19 pandemic. In: Zong, C., Xia, F., Li, W., Navigli, R. (eds.) Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL\/IJCNLP 2021, (Volume 1: Long Papers), Virtual Event, 1\u20136 Aug 2021, pp. 2116\u20132129. Association for Computational Linguistics (2021). https:\/\/doi.org\/10.18653\/v1\/2021.acl-long.165, https:\/\/doi.org\/10.18653\/v1\/2021.acl-long.165","DOI":"10.18653\/v1\/2021.acl-long.165"},{"key":"2_CR110","doi-asserted-by":"crossref","unstructured":"Sachan, T., Pinnaparaju, N., Gupta, M., Varma, V.: SCATE: shared cross attention transformer encoders for multimodal fake news detection. In: Proceedings of the 2021 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 399\u2013406 (2021)","DOI":"10.1145\/3487351.3490965"},{"key":"2_CR111","doi-asserted-by":"crossref","unstructured":"Santia, G.C., Williams, J.R.: BuzzFace: a news veracity dataset with Facebook user commentary and egos. In: Proceedings of the Twelfth International Conference on Web and Social Media, ICWSM 2018, Stanford, California, USA, 25\u201328 June 2018, pp. 531\u2013540. AAAI Press (2018). https:\/\/aaai.org\/ocs\/index.php\/ICWSM\/ICWSM18\/paper\/view\/17825","DOI":"10.1609\/icwsm.v12i1.14985"},{"key":"2_CR112","unstructured":"Sathe, A., Ather, S., Le, T.M., Perry, N., Park, J.: Automated fact-checking of claims from wikipedia. In: Calzolari, N., et al. (eds.) Proceedings of The 12th Language Resources and Evaluation Conference, LREC 2020, Marseille, France, 11\u201316 May 2020, pp. 6874\u20136882. European Language Resources Association (2020). https:\/\/aclanthology.org\/2020.lrec-1.849\/"},{"key":"2_CR113","doi-asserted-by":"crossref","unstructured":"Schlichtkrull, M., Karpukhin, V., O\u011fuz, B., Lewis, M., Yih, W.t., Riedel, S.: Joint verification and reranking for open fact checking over tables. arXiv preprint arXiv:2012.15115 (2020)","DOI":"10.18653\/v1\/2021.acl-long.529"},{"key":"2_CR114","doi-asserted-by":"crossref","unstructured":"Schuster, T., Fisch, A., Barzilay, R.: Get your vitamin C! robust fact verification with contrastive evidence. arXiv preprint arXiv:2103.08541 (2021)","DOI":"10.18653\/v1\/2021.naacl-main.52"},{"key":"2_CR115","doi-asserted-by":"crossref","unstructured":"Schuster, T., Fisch, A., Barzilay, R.: Get your Vitamin C! robust fact verification with contrastive evidence. In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 624\u2013643. Association for Computational Linguistics (2021). https:\/\/www.aclweb.org\/anthology\/2021.naacl-main.52","DOI":"10.18653\/v1\/2021.naacl-main.52"},{"issue":"2","key":"2_CR116","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1162\/coli_a_00380","volume":"46","author":"T Schuster","year":"2020","unstructured":"Schuster, T., Schuster, R., Shah, D.J., Barzilay, R.: The limitations of stylometry for detecting machine-generated fake news. Comput. Linguist. 46(2), 499\u2013510 (2020)","journal-title":"Comput. Linguist."},{"key":"2_CR117","doi-asserted-by":"crossref","unstructured":"Schuster, T., Shah, D.J., Yeo, Y.J.S., Filizzola, D., Santus, E., Barzilay, R.: Towards debiasing fact verification models. arXiv preprint arXiv:1908.05267 (2019)","DOI":"10.18653\/v1\/D19-1341"},{"key":"2_CR118","doi-asserted-by":"crossref","unstructured":"Serrano, S., Smith, N.A.: Is attention interpretable? In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 2931\u20132951 (2019)","DOI":"10.18653\/v1\/P19-1282"},{"key":"2_CR119","doi-asserted-by":"crossref","unstructured":"Shaar, S., Martino, G.D.S., Babulkov, N., Nakov, P.: That is a known lie: detecting previously fact-checked claims. arXiv preprint arXiv:2005.06058 (2020)","DOI":"10.18653\/v1\/2020.acl-main.332"},{"key":"2_CR120","unstructured":"Shahi, G.K., Nandini, D.: FakeCovid\u2013a multilingual cross-domain fact check news dataset for COVID-19 (2020)"},{"issue":"2","key":"2_CR121","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1109\/TKDE.2014.2327028","volume":"27","author":"W Shen","year":"2014","unstructured":"Shen, W., Wang, J., Han, J.: Entity linking with a knowledge base: issues, techniques, and solutions. IEEE Trans. Knowl. Data Eng. 27(2), 443\u2013460 (2014)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"2_CR122","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.knosys.2016.04.015","volume":"104","author":"B Shi","year":"2016","unstructured":"Shi, B., Weninger, T.: Discriminative predicate path mining for fact checking in knowledge graphs. Knowl.-Based Syst. 104, 123\u2013133 (2016)","journal-title":"Knowl.-Based Syst."},{"key":"2_CR123","doi-asserted-by":"crossref","unstructured":"Shoemaker, P.J.: News values: reciprocal effects on journalists and journalism. Int. Encycl. Media Effects, 1\u20139 (2017)","DOI":"10.1002\/9781118783764.wbieme0053"},{"key":"2_CR124","doi-asserted-by":"crossref","unstructured":"Shu, K., Cui, L., Wang, S., Lee, D., Liu, H.: Defend: explainable fake news detection. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 395\u2013405 (2019)","DOI":"10.1145\/3292500.3330935"},{"issue":"3","key":"2_CR125","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1089\/big.2020.0062","volume":"8","author":"K Shu","year":"2020","unstructured":"Shu, K., Mahudeswaran, D., Wang, S., Lee, D., Liu, H.: FakeNewsNet: a data repository with news content, social context, and spatiotemporal information for studying fake news on social media. Big Data 8(3), 171\u2013188 (2020). https:\/\/doi.org\/10.1089\/big.2020.0062","journal-title":"Big Data"},{"issue":"1","key":"2_CR126","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. ACM SIGKDD Explor. Newsl. 19(1), 22\u201336 (2017)","journal-title":"ACM SIGKDD Explor. Newsl."},{"key":"2_CR127","doi-asserted-by":"crossref","unstructured":"Singhal, S., Shah, R.R., Chakraborty, T., Kumaraguru, P., Satoh, S.: SpotFake: a multi-modal framework for fake news detection. In: 2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM), pp. 39\u201347. IEEE (2019)","DOI":"10.1109\/BigMM.2019.00-44"},{"issue":"1","key":"2_CR128","doi-asserted-by":"publisher","first-page":"102437","DOI":"10.1016\/j.ipm.2020.102437","volume":"58","author":"C Song","year":"2021","unstructured":"Song, C., Ning, N., Zhang, Y., Wu, B.: A multimodal fake news detection model based on crossmodal attention residual and multichannel convolutional neural networks. Inf. Process. Manage. 58(1), 102437 (2021)","journal-title":"Inf. Process. Manage."},{"issue":"6","key":"2_CR129","doi-asserted-by":"publisher","first-page":"102712","DOI":"10.1016\/j.ipm.2021.102712","volume":"58","author":"C Song","year":"2021","unstructured":"Song, C., Shu, K., Wu, B.: Temporally evolving graph neural network for fake news detection. Inf. Process. Manage. 58(6), 102712 (2021)","journal-title":"Inf. Process. Manage."},{"key":"2_CR130","doi-asserted-by":"crossref","unstructured":"Starbird, K., Arif, A., Wilson, T., Van Koevering, K., Yefimova, K., Scarnecchia, D.: Ecosystem or echo-system? Exploring content sharing across alternative media domains. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 12 (2018)","DOI":"10.1609\/icwsm.v12i1.15009"},{"key":"2_CR131","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"630","DOI":"10.1007\/978-3-030-30793-6_36","volume-title":"The Semantic Web \u2013 ISWC 2019","author":"ZH Syed","year":"2019","unstructured":"Syed, Z.H., R\u00f6der, M., Ngomo, A.-C.N.: Unsupervised discovery of corroborative paths for fact validation. In: Ghidini, C., et al. (eds.) ISWC 2019. LNCS, vol. 11778, pp. 630\u2013646. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-30793-6_36"},{"key":"2_CR132","doi-asserted-by":"crossref","unstructured":"Tandoc Jr., E.C., Lim, Z.W., Ling, R.: Defining \u201cfake news\u201d a typology of scholarly definitions. Digit. Journal. 6(2), 137\u2013153 (2018)","DOI":"10.1080\/21670811.2017.1360143"},{"key":"2_CR133","unstructured":"Thorne, J., Vlachos, A.: Automated fact checking: task formulations, methods and future directions. arXiv preprint arXiv:1806.07687 (2018)"},{"key":"2_CR134","doi-asserted-by":"crossref","unstructured":"Thorne, J., Vlachos, A.: Elastic weight consolidation for better bias inoculation. arXiv preprint arXiv:2004.14366 (2020)","DOI":"10.18653\/v1\/2021.eacl-main.82"},{"key":"2_CR135","doi-asserted-by":"crossref","unstructured":"Thorne, J., Vlachos, A., Christodoulopoulos, C., Mittal, A.: Fever: a large-scale dataset for fact extraction and verification. arXiv preprint arXiv:1803.05355 (2018)","DOI":"10.18653\/v1\/N18-1074"},{"key":"2_CR136","doi-asserted-by":"publisher","unstructured":"Thorne, J., Vlachos, A., Christodoulopoulos, C., Mittal, A.: FEVER: a large-scale dataset for fact extraction and verification. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 809\u2013819. Association for Computational Linguistics, New Orleans, Louisiana (2018). https:\/\/doi.org\/10.18653\/v1\/N18-1074, https:\/\/www.aclweb.org\/anthology\/N18-1074","DOI":"10.18653\/v1\/N18-1074"},{"key":"2_CR137","doi-asserted-by":"crossref","unstructured":"Thorne, J., Vlachos, A., Cocarascu, O., Christodoulopoulos, C., Mittal, A.: The fact extraction and verification (fever) shared task. arXiv preprint arXiv:1811.10971 (2018)","DOI":"10.18653\/v1\/W18-5501"},{"key":"2_CR138","doi-asserted-by":"crossref","unstructured":"Thorne, J., Vlachos, A., Cocarascu, O., Christodoulopoulos, C., Mittal, A.: The fever2. 0 shared task. In: Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER), pp. 1\u20136 (2019)","DOI":"10.18653\/v1\/D19-6601"},{"issue":"2","key":"2_CR139","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1080\/08913811.2013.843872","volume":"25","author":"JE Uscinski","year":"2013","unstructured":"Uscinski, J.E., Butler, R.W.: The epistemology of fact checking. Crit. Rev. 25(2), 162\u2013180 (2013)","journal-title":"Crit. Rev."},{"issue":"2","key":"2_CR140","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3316809","volume":"13","author":"MD Vicario","year":"2019","unstructured":"Vicario, M.D., Quattrociocchi, W., Scala, A., Zollo, F.: Polarization and fake news: early warning of potential misinformation targets. ACM Trans. Web (TWEB) 13(2), 1\u201322 (2019)","journal-title":"ACM Trans. Web (TWEB)"},{"key":"2_CR141","doi-asserted-by":"crossref","unstructured":"Vlachos, A., Riedel, S.: Fact checking: task definition and dataset construction. In: Proceedings of the ACL 2014 Workshop on Language Technologies and Computational Social Science, pp. 18\u201322 (2014)","DOI":"10.3115\/v1\/W14-2508"},{"key":"2_CR142","doi-asserted-by":"publisher","unstructured":"Vlachos, A., Riedel, S.: Identification and verification of simple claims about statistical properties. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 2596\u20132601. Association for Computational Linguistics, Lisbon, Portugal (2015). https:\/\/doi.org\/10.18653\/v1\/D15-1312, https:\/\/www.aclweb.org\/anthology\/D15-1312","DOI":"10.18653\/v1\/D15-1312"},{"key":"2_CR143","doi-asserted-by":"crossref","unstructured":"Volkova, S., Shaffer, K., Jang, J.Y., Hodas, N.: Separating facts from fiction: Linguistic models to classify suspicious and trusted news posts on twitter. In: Proceedings of the 55th annual meeting of the association for computational linguistics (volume 2: Short papers), pp. 647\u2013653 (2017)","DOI":"10.18653\/v1\/P17-2102"},{"key":"2_CR144","doi-asserted-by":"publisher","unstructured":"Volkova, S., Shaffer, K., Jang, J.Y., Hodas, N.: Separating facts from fiction: linguistic models to classify suspicious and trusted news posts on Twitter. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp. 647\u2013653. Association for Computational Linguistics, Vancouver, Canada (2017). https:\/\/doi.org\/10.18653\/v1\/P17-2102, https:\/\/www.aclweb.org\/anthology\/P17-2102","DOI":"10.18653\/v1\/P17-2102"},{"key":"2_CR145","doi-asserted-by":"crossref","unstructured":"Wadden, D., et al.: Fact or fiction: verifying scientific claims. arXiv preprint arXiv:2004.14974 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.609"},{"key":"2_CR146","doi-asserted-by":"publisher","unstructured":"Wadden, D., et al.: Fact or fiction: verifying scientific claims. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 7534\u20137550. Association for Computational Linguistics (2020). https:\/\/doi.org\/10.18653\/v1\/2020.emnlp-main.609, https:\/\/www.aclweb.org\/anthology\/2020.emnlp-main.609","DOI":"10.18653\/v1\/2020.emnlp-main.609"},{"issue":"3","key":"2_CR147","doi-asserted-by":"publisher","first-page":"1093","DOI":"10.3390\/app12031093","volume":"12","author":"J Wang","year":"2022","unstructured":"Wang, J., Mao, H., Li, H.: FMFN: fine-grained multimodal fusion networks for fake news detection. Appl. Sci. 12(3), 1093 (2022)","journal-title":"Appl. Sci."},{"key":"2_CR148","doi-asserted-by":"publisher","unstructured":"Wang, N.X.R., Mahajan, D., Danilevsky, M., Rosenthal, S.: SemEval-2021 task 9: fact verification and evidence finding for tabular data in scientific documents (SEM-TAB-FACTS). In: Palmer, A., Schneider, N., Schluter, N., Emerson, G., Herbelot, A., Zhu, X. (eds.) Proceedings of the 15th International Workshop on Semantic Evaluation, SemEval@ACL\/IJCNLP 2021, Virtual Event \/ Bangkok, Thailand, 5\u20136 Aug. 2021, pp. 317\u2013326. Association for Computational Linguistics (2021). https:\/\/doi.org\/10.18653\/v1\/2021.semeval-1.39","DOI":"10.18653\/v1\/2021.semeval-1.39"},{"key":"2_CR149","doi-asserted-by":"crossref","unstructured":"Wang, W.Y.: \u201cLiar, liar pants on fire\u201d: a new benchmark dataset for fake news detection. arXiv preprint arXiv:1705.00648 (2017)","DOI":"10.18653\/v1\/P17-2067"},{"key":"2_CR150","doi-asserted-by":"publisher","unstructured":"Wang, W.Y.: \u201cLiar, Liar Pants on Fire\u201d: A new benchmark dataset for fake news detection. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pp. 422\u2013426. Association for Computational Linguistics, Vancouver, Canada (2017). https:\/\/doi.org\/10.18653\/v1\/P17-2067, https:\/\/www.aclweb.org\/anthology\/P17-2067","DOI":"10.18653\/v1\/P17-2067"},{"key":"2_CR151","unstructured":"Wang, Z., Shan, X., Yang, J.: N15news: a new dataset for multimodal news classification. arXiv preprint arXiv:2108.13327 (2021)"},{"key":"2_CR152","unstructured":"Wardle, C., Derakhshan, H.: Information disorder: toward an interdisciplinary framework for research and policymaking (2017)"},{"key":"2_CR153","doi-asserted-by":"crossref","unstructured":"Williams, A., Nangia, N., Bowman, S.R.: A broad-coverage challenge corpus for sentence understanding through inference. arXiv preprint arXiv:1704.05426 (2017)","DOI":"10.18653\/v1\/N18-1101"},{"key":"2_CR154","unstructured":"Williams, E., Rodrigues, P., Novak, V.: Accenture at CheckThat! 2020: if you say so: post-hoc fact-checking of claims using transformer-based models. arXiv preprint arXiv:2009.02431 (2020)"},{"key":"2_CR155","doi-asserted-by":"crossref","unstructured":"Wu, L., Rao, Y., Yang, X., Wang, W., Nazir, A.: Evidence-aware hierarchical interactive attention networks for explainable claim verification. In: Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence, pp. 1388\u20131394 (2021)","DOI":"10.24963\/ijcai.2020\/193"},{"key":"2_CR156","doi-asserted-by":"crossref","unstructured":"Yang, X., Lyu, Y., Tian, T., Liu, Y., Liu, Y., Zhang, X.: Rumor detection on social media with graph structured adversarial learning. In: Proceedings of the Twenty-ninth International Conference on International Joint Conferences on Artificial Intelligence, pp. 1417\u20131423 (2021)","DOI":"10.24963\/ijcai.2020\/197"},{"key":"2_CR157","unstructured":"Zellers, R., et al.: Defending against neural fake news. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"},{"issue":"10","key":"2_CR158","doi-asserted-by":"publisher","first-page":"e12438","DOI":"10.1111\/lnc3.12438","volume":"15","author":"X Zeng","year":"2021","unstructured":"Zeng, X., Abumansour, A.S., Zubiaga, A.: Automated fact-checking: a survey. Lang. Linguist. Compass 15(10), e12438 (2021)","journal-title":"Lang. Linguist. Compass"},{"key":"2_CR159","doi-asserted-by":"crossref","unstructured":"Zhang, J., Dong, B., Philip, S.Y.: FakeDetector: effective fake news detection with deep diffusive neural network. In: 2020 IEEE 36th International Conference on Data Engineering (ICDE), pp. 1826\u20131829. IEEE (2020)","DOI":"10.1109\/ICDE48307.2020.00180"},{"key":"2_CR160","doi-asserted-by":"publisher","unstructured":"Zhang, W., Deng, Y., Ma, J., Lam, W.: AnswerFact: fact checking in product question answering. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 2407\u20132417. Association for Computational Linguistics (2020). https:\/\/doi.org\/10.18653\/v1\/2020.emnlp-main.188, https:\/\/www.aclweb.org\/anthology\/2020.emnlp-main.188","DOI":"10.18653\/v1\/2020.emnlp-main.188"},{"key":"2_CR161","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Ives, Z., Roth, D.: Evidence-based trustworthiness. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 413\u2013423 (2019)","DOI":"10.18653\/v1\/P19-1040"},{"key":"2_CR162","doi-asserted-by":"crossref","unstructured":"Zhong, W., et al.: Reasoning over semantic-level graph for fact checking. arXiv preprint arXiv:1909.03745 (2019)","DOI":"10.18653\/v1\/2020.acl-main.549"},{"issue":"2","key":"2_CR163","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3377478","volume":"1","author":"X Zhou","year":"2020","unstructured":"Zhou, X., Jain, A., Phoha, V.V., Zafarani, R.: Fake news early detection: a theory-driven model. Digit. Threats: Res. Pract. 1(2), 1\u201325 (2020)","journal-title":"Digit. Threats: Res. Pract."},{"key":"2_CR164","doi-asserted-by":"crossref","unstructured":"Zhou, X., Mulay, A., Ferrara, E., Zafarani, R.: Recovery: a multimodal repository for COVID-19 news credibility research. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, pp. 3205\u20133212 (2020)","DOI":"10.1145\/3340531.3412880"},{"issue":"2","key":"2_CR165","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3161603","volume":"51","author":"A Zubiaga","year":"2018","unstructured":"Zubiaga, A., Aker, A., Bontcheva, K., Liakata, M., Procter, R.: Detection and resolution of rumours in social media: a survey. ACM Comput. Surv. (CSUR) 51(2), 1\u201336 (2018)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"2_CR166","doi-asserted-by":"crossref","unstructured":"Zubiaga, A., Liakata, M., Procter, R., Wong Sak Hoi, G., Tolmie, P.: Analysing how people orient to and spread rumours in social media by looking at conversational threads. PloS one 11(3), e0150989 (2016)","DOI":"10.1371\/journal.pone.0150989"},{"key":"2_CR167","unstructured":"Zuo, C., Karakas, A., Banerjee, R.: A hybrid recognition system for check-worthy claims using heuristics and supervised learning. In: CEUR Workshop Proceedings, vol. 2125 (2018)"}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Pervasive Knowledge and Collective Intelligence on Web and Social Media"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-31469-8_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,19]],"date-time":"2024-10-19T09:37:59Z","timestamp":1729330679000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-31469-8_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031314681","9783031314698"],"references-count":167,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-31469-8_2","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"28 April 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PerSOM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pervasive Knowledge and Collective Intelligence on Web and Social Media","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Messina","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":"17 November 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 November 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"persom2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Confy Plus","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"35","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"9","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"26% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}