{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T14:17:03Z","timestamp":1784125023413,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":23,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819698806","type":"print"},{"value":"9789819698813","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-9881-3_10","type":"book-chapter","created":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T21:16:00Z","timestamp":1753391760000},"page":"111-122","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DAHAE-MFFN: Dynamic Association Hypergraph Attention Enhanced Multimodal Feature Fusion Network"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-3979-7993","authenticated-orcid":false,"given":"Xinyu","family":"Zheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3928-4960","authenticated-orcid":false,"given":"Yicun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2542-6603","authenticated-orcid":false,"given":"Xianguo","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,25]]},"reference":[{"key":"10_CR1","doi-asserted-by":"crossref","unstructured":"Wu, Y., Zhan, P., Zhang, Y., Wang, L., Xu, Z.: Multimodal fusion with co-attention networks for fake news detection. In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pp. 2560\u20132569 (2021)","DOI":"10.18653\/v1\/2021.findings-acl.226"},{"key":"10_CR2","doi-asserted-by":"crossref","unstructured":"Zheng, J., Zhang, X., Guo, S., Wang, Q., Zang, W., Zhang, Y.: MFAN: multi-modal feature-enhanced attention networks for rumor detection. In: IJCAI, pp. 2413\u20132419 (2022)","DOI":"10.24963\/ijcai.2022\/335"},{"key":"10_CR3","doi-asserted-by":"crossref","unstructured":"Yuan, C., Ma, Q., Zhou, W., Han, J., Hu, S.: Jointly embedding the local and global relations of heterogeneous graph for rumor detection. In: 2019 IEEE International Conference on Data Mining (ICDM), pp. 796\u2013805. IEEE (2019)","DOI":"10.1109\/ICDM.2019.00090"},{"key":"10_CR4","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)"},{"key":"10_CR5","unstructured":"Veli\u010dkovi\u0107, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., Bengio, Y.: Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)"},{"key":"10_CR6","unstructured":"Ma, J., et al.: Detecting rumors from microblogs with recurrent neural networks. In: AAAI Press (2016)"},{"key":"10_CR7","doi-asserted-by":"crossref","unstructured":"Yu, F., Liu, Q., Wu, S., Wang, L., Tan, T.: A convolutional approach for misinformation identification. In: IJCAI, pp. 3901\u20133907 (2017)","DOI":"10.24963\/ijcai.2017\/545"},{"key":"10_CR8","doi-asserted-by":"crossref","unstructured":"Liu, Y., Wu, Y.F.: Early detection of fake news on social media through propagation path classification with recurrent and convolutional networks. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32, no. 1 (2018)","DOI":"10.1609\/aaai.v32i1.11268"},{"key":"10_CR9","doi-asserted-by":"crossref","unstructured":"Shu, K., Mahudeswaran, D., Wang, S., Liu, H.: Hierarchical propagation networks for fake news detection: Investigation and exploitation. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 14, pp. 626\u2013637 (2020)","DOI":"10.1609\/icwsm.v14i1.7329"},{"key":"10_CR10","doi-asserted-by":"crossref","unstructured":"Zhang, H., Fang, Q., Qian, S., Xu, C.: Multi-modal knowledge-aware event memory network for social media rumor detection. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 1942\u20131951. ACM (2019)","DOI":"10.1145\/3343031.3350850"},{"issue":"5","key":"10_CR11","doi-asserted-by":"publisher","first-page":"102610","DOI":"10.1016\/j.ipm.2021.102610","volume":"58","author":"J Xue","year":"2021","unstructured":"Xue, J., Wang, Y., Tian, Y., Li, Y., Shi, L., Wei, L.: Detecting fake news by exploring the consistency of multimodal data. Inf. Process. Manage. 58(5), 102610 (2021)","journal-title":"Inf. Process. Manage."},{"key":"10_CR12","doi-asserted-by":"crossref","unstructured":"Xie, J., Liu, S., Liu, R., Zhang, Y., Zhu, Y.: SeRN: stance extraction and reasoning network for fake news detection. In: ICASSP 2021\u20132021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2520\u20132524. IEEE (2021)","DOI":"10.1109\/ICASSP39728.2021.9414787"},{"key":"10_CR13","doi-asserted-by":"crossref","unstructured":"Yu, J., Huang, Q., Zhou, X., Sha, Y.: Iarnet: an information aggregating and reasoning network over heterogeneous graph for fake news detection. In: 2020 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20139. IEEE (2020)","DOI":"10.1109\/IJCNN48605.2020.9207406"},{"key":"10_CR14","doi-asserted-by":"crossref","unstructured":"Khoo, L.M.S., Chieu, H.L., Qian, Z., Jiang, J.: Interpretable rumor detection in microblogs by attending to user interactions. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 05, pp. 8783\u20138790 (2020)","DOI":"10.1609\/aaai.v34i05.6405"},{"key":"10_CR15","doi-asserted-by":"crossref","unstructured":"Bian, T., et al.: Rumor detection on social media with bi-directional graph convolutional networks. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 01, pp. 549\u2013556 (2020)","DOI":"10.1609\/aaai.v34i01.5393"},{"key":"10_CR16","unstructured":"Ma, J., Gao, W., Mitra, P., et al.: Detecting rumors from microblogs with recurrent neural networks. In: International Joint Conference on Artificial Intelligence, AAAI Press (2016)"},{"key":"10_CR17","doi-asserted-by":"crossref","unstructured":"Zubiaga, A., Liakata, M., Procter, R.: Exploiting context for rumour detection in social media. In: Social Informatics: 9th International Conference, SocInfo 2017, Oxford, UK, September 13\u201315, 2017, Proceedings, Part I 9, pp. 109\u2013123. Springer (2017)","DOI":"10.1007\/978-3-319-67217-5_8"},{"key":"10_CR18","doi-asserted-by":"crossref","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. ACM (2019)","DOI":"10.1145\/3308558.3313552"},{"key":"10_CR19","doi-asserted-by":"crossref","unstructured":"Zhou, X., Wu, J., Zafarani, R.: SAFE: similarity-aware multi-modal fake news detection. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 354\u2013367. Springer (2020)","DOI":"10.1007\/978-3-030-47436-2_27"},{"key":"10_CR20","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":"10_CR21","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. ACM (2021)","DOI":"10.1145\/3404835.3462871"},{"key":"10_CR22","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Yang, Y., Ying, Q., Qian, Z., Zhang, X.: Multi-modal fake news detection on social media via multi-grained information fusion. In: Proceedings of the 2023 ACM International Conference on Multimedia Retrieval, pp. 343\u2013352. ACM (2023)","DOI":"10.1145\/3591106.3592271"},{"key":"10_CR23","doi-asserted-by":"publisher","first-page":"120310","DOI":"10.1016\/j.ins.2024.120310","volume":"664","author":"L Hu","year":"2024","unstructured":"Hu, L., Zhao, Z., Qi, W., Song, X., Nie, L.: Multimodal matching-aware co-attention networks with mutual knowledge distillation for fake news detection. Inf. Sci. 664, 120310 (2024)","journal-title":"Inf. Sci."}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-9881-3_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T13:52:01Z","timestamp":1784123521000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-9881-3_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819698806","9789819698813"],"references-count":23,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-9881-3_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"25 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ningbo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}