{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T08:08:30Z","timestamp":1767773310289,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031442155"},{"type":"electronic","value":"9783031442162"}],"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\/978-3-031-44216-2_24","type":"book-chapter","created":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T07:02:58Z","timestamp":1695279778000},"page":"291-303","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["BGEK: External Knowledge-Enhanced Graph Convolutional Networks for\u00a0Rumor Detection in\u00a0Online Social Networks"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-8322-2037","authenticated-orcid":false,"given":"Xiaoda","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3866-5200","authenticated-orcid":false,"given":"Chenxiang","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0672-7651","authenticated-orcid":false,"given":"Tengda","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7857-6675","authenticated-orcid":false,"given":"Zhangrui","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1778-8039","authenticated-orcid":false,"given":"Jiongyan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1197-5906","authenticated-orcid":false,"given":"Haizhou","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,9,22]]},"reference":[{"key":"24_CR1","doi-asserted-by":"crossref","unstructured":"Bian, T., et al.: Rumor detection on social media with bi-directional graph convolutional networks. In: Proceedings of the 34th AAAI Conference on Artificial Intelligence, pp. 549\u2013556 (2020)","DOI":"10.1609\/aaai.v34i01.5393"},{"key":"24_CR2","doi-asserted-by":"crossref","unstructured":"Castillo, C., Mendoza, M., Poblete, B.: Information credibility on twitter. In: Proceedings of the 20th International Conference on World Wide Web, pp. 675\u2013684 (2011)","DOI":"10.1145\/1963405.1963500"},{"key":"24_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119347","volume":"215","author":"X Chen","year":"2023","unstructured":"Chen, X., Wang, H., Ke, L., Lu, Z., Su, H., Chen, X.: Identifying cantonese rumors with discriminative feature integration in online social networks. Expert Syst. Appl. 215, 119347 (2023)","journal-title":"Expert Syst. Appl."},{"key":"24_CR4","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"24_CR5","doi-asserted-by":"crossref","unstructured":"Fionda, V., Pirr\u00f2, G.: Fact checking via evidence patterns. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence, pp. 3755\u20133761 (2018)","DOI":"10.24963\/ijcai.2018\/522"},{"key":"24_CR6","doi-asserted-by":"crossref","unstructured":"Hu, L., et al.: Compare to the knowledge: graph neural fake news detection with external knowledge. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, pp. 754\u2013763 (2021)","DOI":"10.18653\/v1\/2021.acl-long.62"},{"key":"24_CR7","doi-asserted-by":"crossref","unstructured":"Ke, L., Chen, X., Lu, Z., Su, H., Wang, H.: A novel approach for cantonese rumor detection based on deep neural network. In: Proceedings of 33rd IEEE International Conference on Systems, Man, and Cybernetics, pp. 1610\u20131615 (2020)","DOI":"10.1109\/SMC42975.2020.9283056"},{"key":"24_CR8","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"24_CR9","doi-asserted-by":"crossref","unstructured":"Kwon, S., Cha, M., Jung, K., Chen, W., Wang, Y.: Prominent features of rumor propagation in online social media. In: Proceedings of 13th IEEE International Conference on Data Mining, pp. 1103\u20131108 (2013)","DOI":"10.1109\/ICDM.2013.61"},{"key":"24_CR10","doi-asserted-by":"crossref","unstructured":"Lin, Z.H., Wang, Z., Zhao, M., Song, Y., Lan, L.: An AI-based system to assist human fact-checkers for labeling cantonese fake news on social media. In: Proceedings of 10th IEEE International Conference on Big Data, pp. 6766\u20136768 (2022)","DOI":"10.1109\/BigData55660.2022.10020949"},{"key":"24_CR11","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. In: Proceedings of 58th Annual Meeting of the Association for Computational Linguistics, pp. 505\u2013514 (2020)","DOI":"10.18653\/v1\/2020.acl-main.48"},{"key":"24_CR12","unstructured":"Ma, J., et al.: Detecting rumors from microblogs with recurrent neural networks. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence, pp. 3818\u20133824 (2016)"},{"key":"24_CR13","doi-asserted-by":"crossref","unstructured":"Ma, J., Gao, W., Wong, K.F.: Rumor detection on twitter with tree-structured recursive neural networks. In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp. 1980\u20131989 (2018)","DOI":"10.18653\/v1\/P18-1184"},{"key":"24_CR14","doi-asserted-by":"crossref","unstructured":"Pan, J.Z., Pavlova, S., Li, C., Li, N., Li, Y., Liu, J.: Content based fake news detection using knowledge graphs. In: The Semantic Web-ISWC : 17th International Semantic Web Conference, pp. 669\u2013683 (2018)","DOI":"10.1007\/978-3-030-00671-6_39"},{"key":"24_CR15","doi-asserted-by":"crossref","unstructured":"Song, Y.Z., Chen, Y.S., Chang, Y.T., Weng, S.Y., Shuai, H.H.: Adversary-aware rumor detection. In: Proceedings of the 59th Findings of the Association for Computational Linguistics: ACL-IJCNLP, pp. 1371\u20131382 (2021)","DOI":"10.18653\/v1\/2021.findings-acl.118"},{"key":"24_CR16","doi-asserted-by":"crossref","unstructured":"Sun, M., Zhang, X., Zheng, J., Ma, G.: DDGCN: dual dynamic graph convolutional networks for rumor detection on social media. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence, vol. 36, pp. 4611\u20134619 (2022)","DOI":"10.1609\/aaai.v36i4.20385"},{"key":"24_CR17","doi-asserted-by":"crossref","unstructured":"Sun, T., Qian, Z., Dong, S., Li, P., Zhu, Q.: Rumor detection on social media with graph adversarial contrastive learning. In: Proceedings of the 31st ACM Web Conference, pp. 2789\u20132797 (2022)","DOI":"10.1145\/3485447.3511999"},{"key":"24_CR18","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"24_CR19","doi-asserted-by":"crossref","unstructured":"Wei, L., Hu, D., Zhou, W., Yue, Z., Hu, S.: Towards propagation uncertainty: Edge-enhanced bayesian graph convolutional networks for rumor detection. arXiv preprint arXiv:2107.11934 (2021)","DOI":"10.18653\/v1\/2021.acl-long.297"},{"key":"24_CR20","doi-asserted-by":"crossref","unstructured":"Wu, K., Yang, S., Zhu, K.Q.: False rumors detection on sina weibo by propagation structures. In: Proceedings of the 31st IEEE International Conference on Data Engineering, pp. 651\u2013662 (2015)","DOI":"10.1109\/ICDE.2015.7113322"},{"key":"24_CR21","doi-asserted-by":"crossref","unstructured":"Yu, F., Liu, Q., Wu, S., Wang, L., Tan, T.: A convolutional approach for misinformation identification. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence, pp. 3901\u20133907 (2017)","DOI":"10.24963\/ijcai.2017\/545"},{"key":"24_CR22","doi-asserted-by":"crossref","unstructured":"Zhou, P., et al.: Attention-based bidirectional long short-term memory networks for relation classification. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, pp. 207\u2013212 (2016)","DOI":"10.18653\/v1\/P16-2034"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2023"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-44216-2_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T07:06:37Z","timestamp":1695279997000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-44216-2_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031442155","9783031442162"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-44216-2_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"22 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Heraklion","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","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":"26 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"32","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easyacademia.org","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"947","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":"426","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":"22","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":"45% - 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":"2.4","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":"4","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)"}},{"value":"type of other papers accepted  : 9 Abstract","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}