{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T11:46:07Z","timestamp":1762429567870,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":29,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,12,27]],"date-time":"2023-12-27T00:00:00Z","timestamp":1703635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Innovation Theory Technology Group Fund of China Electronics Tian'ao Co., Ltd"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,12,27]]},"DOI":"10.1145\/3639479.3639486","type":"proceedings-article","created":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T07:55:51Z","timestamp":1709106951000},"page":"27-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["EEGCN: Event Evolutionary Graph Comparison Network for Multi-Modal Fake News Detection"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1019-4238","authenticated-orcid":false,"given":"Xiang","family":"Dai","sequence":"first","affiliation":[{"name":"Southwest China Institute of Electronic Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8373-3254","authenticated-orcid":false,"given":"Yue","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-5427-9370","authenticated-orcid":false,"given":"Xin","family":"Liu","sequence":"additional","affiliation":[{"name":"Southwest China Institute of Electronic Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8346-8925","authenticated-orcid":false,"given":"Dan","family":"Song","sequence":"additional","affiliation":[{"name":"Southwest China Institute of Electronic Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6428-2535","authenticated-orcid":false,"given":"Zhaobo","family":"Juan","sequence":"additional","affiliation":[{"name":"Southwest China Institute of Electronic Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8606-8419","authenticated-orcid":false,"given":"Shengze","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3448-5664","authenticated-orcid":false,"given":"Liangyu","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4837-9956","authenticated-orcid":false,"given":"Haibo","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-3720-7265","authenticated-orcid":false,"given":"Jing","family":"Shen","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Harbin Engineering University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,2,28]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5393"},{"key":"e_1_3_2_1_2_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_3_1","volume-title":"Game-on: Graph attention network based multimodal fusion for fake news detection. arXiv preprint arXiv:2202.12478","author":"Dhawan Mudit","year":"2022","unstructured":"Mudit Dhawan, Shakshi Sharma, Aditya Kadam, Rajesh Sharma, and Ponnurangam Kumaraguru. 2022. Game-on: Graph attention network based multimodal fusion for fake news detection. arXiv preprint arXiv:2202.12478 (2022)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462990"},{"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","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10344"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3463001"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.62"},{"key":"e_1_3_2_1_10_1","volume-title":"CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking. arXiv preprint arXiv:2206.11863","author":"Hu Xuming","year":"2022","unstructured":"Xuming Hu, Zhijiang Guo, Guanyu Wu, Aiwei Liu, Lijie Wen, and Philip\u00a0S Yu. 2022. CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking. arXiv preprint arXiv:2206.11863 (2022)."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32233-5_49"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123454"},{"key":"e_1_3_2_1_13_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_14_1","volume-title":"Constructing narrative event evolutionary graph for script event prediction. arXiv preprint arXiv:1805.05081","author":"Li Zhongyang","year":"2018","unstructured":"Zhongyang Li, Xiao Ding, and Ting Liu. 2018. Constructing narrative event evolutionary graph for script event prediction. arXiv preprint arXiv:1805.05081 (2018)."},{"key":"e_1_3_2_1_15_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_16_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_17_1","volume-title":"A stylometric inquiry into hyperpartisan and fake news. arXiv preprint arXiv:1702.05638","author":"Potthast Martin","year":"2017","unstructured":"Martin Potthast, Johannes Kiesel, Kevin Reinartz, Janek Bevendorff, and Benno Stein. 2017. A stylometric inquiry into hyperpartisan and fake news. arXiv preprint arXiv:1702.05638 (2017)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5386"},{"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":"FEVER: a large-scale dataset for fact extraction and VERification. arXiv preprint arXiv:1803.05355","author":"Thorne James","year":"2018","unstructured":"James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal. 2018. FEVER: a large-scale dataset for fact extraction and VERification. arXiv preprint arXiv:1803.05355 (2018)."},{"key":"e_1_3_2_1_22_1","volume-title":"Do sentence interactions matter? leveraging sentence level representations for fake news classification. arXiv preprint arXiv:1910.12203","author":"Vaibhav Vaibhav","year":"2019","unstructured":"Vaibhav Vaibhav, Raghuram\u00a0Mandyam Annasamy, and Eduard Hovy. 2019. Do sentence interactions matter? leveraging sentence level representations for fake news classification. arXiv preprint arXiv:1910.12203 (2019)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219903"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3372278.3390713"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2015.7113322"},{"key":"e_1_3_2_1_26_1","first-page":"2560","article-title":"Multimodal fusion with co-attention networks for fake news detection. In Findings of the association for computational linguistics","volume":"2021","author":"Wu Yang","year":"2021","unstructured":"Yang Wu, Pengwei Zhan, Yunjian Zhang, Liming Wang, and Zhen Xu. 2021. Multimodal fusion with co-attention networks for fake news detection. In Findings of the association for computational linguistics: ACL-IJCNLP 2021. 2560\u20132569.","journal-title":"ACL-IJCNLP"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591879"},{"key":"e_1_3_2_1_28_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_29_1","volume-title":"Pacific-Asia Conference on knowledge discovery and data mining. Springer, 354\u2013367","author":"Zhou Xinyi","year":"2020","unstructured":"Xinyi Zhou, Jindi Wu, and Reza Zafarani. 2020. : Similarity-Aware Multi-modal Fake News Detection. In Pacific-Asia Conference on knowledge discovery and data mining. Springer, 354\u2013367."}],"event":{"name":"MLNLP 2023: 2023 6th International Conference on Machine Learning and Natural Language Processing","acronym":"MLNLP 2023","location":"Sanya China"},"container-title":["Proceedings of the 2023 6th International Conference on Machine Learning and Natural Language Processing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3639479.3639486","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3639479.3639486","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T23:53:59Z","timestamp":1755906839000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3639479.3639486"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,27]]},"references-count":29,"alternative-id":["10.1145\/3639479.3639486","10.1145\/3639479"],"URL":"https:\/\/doi.org\/10.1145\/3639479.3639486","relation":{},"subject":[],"published":{"date-parts":[[2023,12,27]]},"assertion":[{"value":"2024-02-28","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}