{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T19:03:00Z","timestamp":1772910180927,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":37,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T00:00:00Z","timestamp":1686528000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100017052","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62276177,62006167,61836007"],"award-info":[{"award-number":["62276177,62006167,61836007"]}],"id":[{"id":"10.13039\/100017052","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,6,12]]},"DOI":"10.1145\/3591106.3592250","type":"proceedings-article","created":{"date-parts":[[2023,6,8]],"date-time":"2023-06-08T22:33:38Z","timestamp":1686263618000},"page":"316-324","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Graph Interactive Network with Adaptive Gradient for Multi-Modal Rumor Detection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2500-760X","authenticated-orcid":false,"given":"Tiening","family":"Sun","sequence":"first","affiliation":[{"name":"Soochow University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7651-7872","authenticated-orcid":false,"given":"Zhong","family":"Qian","sequence":"additional","affiliation":[{"name":"Soochow University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4850-3128","authenticated-orcid":false,"given":"Peifeng","family":"Li","sequence":"additional","affiliation":[{"name":"Soochow University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2708-8976","authenticated-orcid":false,"given":"Qiaoming","family":"Zhu","sequence":"additional","affiliation":[{"name":"Soochow University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,6,12]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1257\/jep.31.2.211"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5393"},{"key":"e_1_3_2_1_3_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_1_4_1","volume-title":"An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929","author":"Dosovitskiy Alexey","year":"2020","unstructured":"Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i1.16080"},{"key":"e_1_3_2_1_6_1","volume-title":"The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval.","author":"He Z.","unstructured":"Z. He, C. Li, F. Zhou, and Y. Yang. 2021. Rumor Detection on Social Media with Event Augmentations. In SIGIR \u201921: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123454"},{"key":"e_1_3_2_1_8_1","volume-title":"Deep learning with python","author":"Ketkar Nikhil","unstructured":"Nikhil Ketkar. 2017. Introduction to pytorch. In Deep learning with python. Springer, 195\u2013208."},{"key":"e_1_3_2_1_9_1","volume-title":"Mvae: Multimodal variational autoencoder for fake news detection. In The world wide web conference. 2915\u20132921.","author":"Khattar Dhruv","year":"2019","unstructured":"Dhruv Khattar, Jaipal\u00a0Singh Goud, Manish Gupta, and Vasudeva Varma. 2019. Mvae: Multimodal variational autoencoder for fake news detection. In The world wide web conference. 2915\u20132921."},{"key":"e_1_3_2_1_10_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf N","year":"2016","unstructured":"Thomas\u00a0N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_1_11_1","volume-title":"Fake news: Evidence from financial markets. Available at SSRN 3237763","author":"Kogan Shimon","year":"2019","unstructured":"Shimon Kogan, Tobias\u00a0J Moskowitz, and Marina Niessner. 2019. Fake news: Evidence from financial markets. Available at SSRN 3237763 (2019)."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1113"},{"key":"e_1_3_2_1_13_1","volume-title":"GCAN: Graph-aware co-attention networks for explainable fake news detection on social media. arXiv preprint arXiv:2004.11648","author":"Lu Yi-Ju","year":"2020","unstructured":"Yi-Ju Lu and Cheng-Te Li. 2020. GCAN: Graph-aware co-attention networks for explainable fake news detection on social media. arXiv preprint arXiv:2004.11648 (2020)."},{"key":"e_1_3_2_1_14_1","unstructured":"Jing Ma Wei Gao Prasenjit Mitra Sejeong Kwon Bernard\u00a0J Jansen Kam-Fai Wong and Meeyoung Cha. 2016. Detecting rumors from microblogs with recurrent neural networks. (2016)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3184558.3188729"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313741"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00806"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI.2018.00021"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3481548"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462871"},{"key":"e_1_3_2_1_21_1","volume-title":"Exploiting tri-relationship for fake news detection. arXiv preprint arXiv:1712.07709 8","author":"Shu Kai","year":"2017","unstructured":"Kai Shu, Suhang Wang, and Huan Liu. 2017. Exploiting tri-relationship for fake news detection. arXiv preprint arXiv:1712.07709 8 (2017)."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.122"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3511999"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411890"},{"key":"e_1_3_2_1_25_1","volume-title":"FANG: Leveraging Social Context for Fake News Detection Using Graph Representation.","author":"NGUYEN","year":"2020","unstructured":"NGUYEN VAN\u00a0HA, K Sugiyama, P Nakov, and MY Kan. 2020. FANG: Leveraging Social Context for Fake News Detection Using Graph Representation. (2020)."},{"key":"e_1_3_2_1_26_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan\u00a0N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01271"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219903"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3372278.3390713"},{"key":"e_1_3_2_1_30_1","volume-title":"Modeling conversation structure and temporal dynamics for jointly predicting rumor stance and veracity. arXiv preprint arXiv:1909.08211","author":"Wei Penghui","year":"2019","unstructured":"Penghui Wei, Nan Xu, and Wenji Mao. 2019. Modeling conversation structure and temporal dynamics for jointly predicting rumor stance and veracity. arXiv preprint arXiv:1909.08211 (2019)."},{"key":"e_1_3_2_1_31_1","volume-title":"DTCA: Decision tree-based co-attention networks for explainable claim verification. arXiv preprint arXiv:2004.13455","author":"Wu Lianwei","year":"2020","unstructured":"Lianwei Wu, Yuan Rao, Yongqiang Zhao, Hao Liang, and Ambreen Nazir. 2020. DTCA: Decision tree-based co-attention networks for explainable claim verification. arXiv preprint arXiv:2004.13455 (2020)."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-acl.226"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.727"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Feng Yu Qiang Liu Shu Wu Liang Wang Tieniu Tan 2017. A Convolutional Approach for Misinformation Identification.. In IJCAI. 3901\u20133907.","DOI":"10.24963\/ijcai.2017\/545"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2019.00090"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3065498"},{"key":"e_1_3_2_1_37_1","volume-title":"MFAN: Multi-modal Feature-enhanced Attention Networks for Rumor Detection. In IJCAI. 2413\u20132419.","author":"Zheng Jiaqi","year":"2022","unstructured":"Jiaqi Zheng, Xi Zhang, Sanchuan Guo, Quan Wang, Wenyu Zang, and Yongdong Zhang. 2022. MFAN: Multi-modal Feature-enhanced Attention Networks for Rumor Detection. In IJCAI. 2413\u20132419."}],"event":{"name":"ICMR '23: International Conference on Multimedia Retrieval","location":"Thessaloniki Greece","acronym":"ICMR '23","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 2023 ACM International Conference on Multimedia Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3591106.3592250","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3591106.3592250","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:30Z","timestamp":1750178250000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3591106.3592250"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,12]]},"references-count":37,"alternative-id":["10.1145\/3591106.3592250","10.1145\/3591106"],"URL":"https:\/\/doi.org\/10.1145\/3591106.3592250","relation":{},"subject":[],"published":{"date-parts":[[2023,6,12]]},"assertion":[{"value":"2023-06-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}