{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T05:45:57Z","timestamp":1763531157055,"version":"3.45.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:00:00Z","timestamp":1755820800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:00:00Z","timestamp":1755820800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the Nation Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62466029","62266028"],"award-info":[{"award-number":["62466029","62266028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"the Yunnan Natural Science Funds","award":["202201AT070157"],"award-info":[{"award-number":["202201AT070157"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1007\/s10115-025-02527-x","type":"journal-article","created":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T08:30:26Z","timestamp":1755851426000},"page":"10137-10160","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Early detection of fake news by integrating global structure and publisher credibility"],"prefix":"10.1007","volume":"67","author":[{"given":"Hongbin","family":"Wang","sequence":"first","affiliation":[]},{"given":"Ye","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yantuan","family":"Xian","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,22]]},"reference":[{"key":"2527_CR1","doi-asserted-by":"crossref","unstructured":"Min E, Rong Y, Bian Y, Xu T, Zhao P, Huang J, Ananiadou S (2022) Divide-and-conquer: post-user interaction network for fake news detection on social media. In: Proceedings of the ACM Web Conference 2022, pp. 1148\u20131158","DOI":"10.1145\/3485447.3512163"},{"key":"2527_CR2","doi-asserted-by":"crossref","unstructured":"Potthast M, Kiesel J, Reinartz K, Bevendorff J, Stein B (2017) A stylometric inquiry into hyperpartisan and fake news. arXiv preprint arXiv:1702.05638","DOI":"10.18653\/v1\/P18-1022"},{"key":"2527_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119291","volume":"213","author":"Y Guo","year":"2023","unstructured":"Guo Y, Ji S, Cao N, Chiu DK, Su N, Zhang C (2023) Mdg: fusion learning of the maximal diffusion, deep propagation and global structure features of fake news. Expert Syst Appl 213:119291","journal-title":"Expert Syst Appl"},{"key":"2527_CR4","doi-asserted-by":"crossref","unstructured":"Ma J, Gao W, Wong K-F (2018) Rumor detection on twitter with tree-structured recursive neural networks. Association for Computational Linguistics","DOI":"10.18653\/v1\/P18-1184"},{"key":"2527_CR5","doi-asserted-by":"crossref","unstructured":"Sun L, Rao Y, Lan Y, Xia B, Li Y (2023) Hg-sl: jointly learning of global and local user spreading behavior for fake news early detection. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, pp. 5248\u20135256","DOI":"10.1609\/aaai.v37i4.25655"},{"key":"2527_CR6","unstructured":"Shu K, Zheng G, Li Y, Mukherjee S, Awadallah AH, Ruston S, Liu H (2020) Leveraging multi-source weak social supervision for early detection of fake news. arXiv preprint arXiv:2004.01732"},{"key":"2527_CR7","unstructured":"Nan Q, Sheng Q, Cao J, Zhu Y, Wang D, Yang G, Li J (2023) Exploiting user comments for early detection of fake news prior to users\u2019 commenting. arXiv preprint arXiv:2310.10429"},{"issue":"6380","key":"2527_CR8","doi-asserted-by":"publisher","first-page":"1146","DOI":"10.1126\/science.aap9559","volume":"359","author":"S Vosoughi","year":"2018","unstructured":"Vosoughi S, Roy D, Aral S (2018) The spread of true and false news online. Science 359(6380):1146\u20131151","journal-title":"Science"},{"key":"2527_CR9","doi-asserted-by":"crossref","unstructured":"Sitaula N, Mohan CK, Grygiel J, Zhou X, Zafarani R (2020) Credibility-based fake news detection. Disinformation, misinformation, and fake news in social media: Emerging research challenges and Opportunities, 163\u2013182","DOI":"10.1007\/978-3-030-42699-6_9"},{"key":"2527_CR10","doi-asserted-by":"crossref","unstructured":"Popat K, Mukherjee S, Yates A, Weikum G (2018) Declare: Debunking fake news and false claims using evidence-aware deep learning. arXiv preprint arXiv:1809.06416","DOI":"10.18653\/v1\/D18-1003"},{"key":"2527_CR11","unstructured":"Wang W (2021) A new benchmark dataset for fake news detection. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, vol. 2"},{"issue":"12","key":"2527_CR12","doi-asserted-by":"publisher","first-page":"2250058","DOI":"10.1142\/S0129065722500587","volume":"32","author":"DP Kasseropoulos","year":"2022","unstructured":"Kasseropoulos DP, Koukaras P, Tjortjis C (2022) Exploiting textual information for fake news detection. Int J Neural Syst 32(12):2250058","journal-title":"Int J Neural Syst"},{"key":"2527_CR13","doi-asserted-by":"crossref","unstructured":"Horne B, Adali S (2017) This just in: Fake news packs a lot in title, uses simpler, repetitive content in text body, more similar to satire than real news. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 11, pp. 759\u2013766","DOI":"10.1609\/icwsm.v11i1.14976"},{"key":"2527_CR14","doi-asserted-by":"crossref","unstructured":"Castillo C, Mendoza M, Poblete B (2011) Information credibility on twitter. In: Proceedings of the 20th International Conference on World Wide Web, pp. 675\u2013684","DOI":"10.1145\/1963405.1963500"},{"issue":"1","key":"2527_CR15","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 (2017) Fake news detection on social media: a data mining perspective. ACM SIGKDD Explorations Newsl 19(1):22\u201336","journal-title":"ACM SIGKDD Explorations Newsl"},{"key":"2527_CR16","doi-asserted-by":"crossref","unstructured":"Amri S, Boleilanga H-CM, Aimeur E (2023) Exfake: towards an explainable fake news detection based on content and social context information. In: 2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE), pp. 01\u201308. IEEE","DOI":"10.1109\/CSCE60160.2023.00373"},{"issue":"1","key":"2527_CR17","first-page":"8836476","volume":"2023","author":"L Fu","year":"2023","unstructured":"Fu L, Liu S (2023) Multimodal fake news detection incorporating external knowledge and user interaction feature. Adv Multimed 2023(1):8836476","journal-title":"Adv Multimed"},{"key":"2527_CR18","doi-asserted-by":"crossref","unstructured":"Kwon S, Cha M, Jung K, Chen W, Wang Y (2013) Prominent features of rumor propagation in online social media. In: 2013 IEEE 13th International Conference on Data Mining, pp. 1103\u20131108. IEEE","DOI":"10.1109\/ICDM.2013.61"},{"key":"2527_CR19","doi-asserted-by":"crossref","unstructured":"Liu Y, Wu Y-F (2018) 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","DOI":"10.1609\/aaai.v32i1.11268"},{"key":"2527_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.123350","volume":"247","author":"AAB Cavalcante","year":"2024","unstructured":"Cavalcante AAB, Freire PMS, Goldschmidt RR, Justel CM (2024) Early detection of fake news on virtual social networks: a time-aware approach based on crowd signals. Expert Syst Appl 247:123350","journal-title":"Expert Syst Appl"},{"key":"2527_CR21","doi-asserted-by":"crossref","unstructured":"Ma J, Gao W, Wong K-F (2017) Detect rumors in microblog posts using propagation structure via kernel learning. Assoc Comput Linguistics","DOI":"10.18653\/v1\/P17-1066"},{"key":"2527_CR22","unstructured":"Wei L, Hu D, Lai Y, Zhou W, Hu S (2022) A unified propagation forest-based framework for fake news detection. In: Proceedings of the 29th International Conference on Computational Linguistics, pp. 2769\u20132779"},{"key":"2527_CR23","doi-asserted-by":"crossref","unstructured":"Ching C-W, Hu L (2024) Decaffe: Dht tree-based online federated fake news detection. In: Proceedings of the 2024 8th International Conference on Control Engineering and Artificial Intelligence, pp. 102\u2013108","DOI":"10.1145\/3640824.3640840"},{"key":"2527_CR24","doi-asserted-by":"crossref","unstructured":"Bian T, Xiao X, Xu T, Zhao P, Huang W, Rong Y, Huang J (2020) Rumor detection on social media with bi-directional graph convolutional networks. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 549\u2013556","DOI":"10.1609\/aaai.v34i01.5393"},{"issue":"4","key":"2527_CR25","doi-asserted-by":"publisher","first-page":"82","DOI":"10.3390\/computation12040082","volume":"12","author":"K Soga","year":"2024","unstructured":"Soga K, Yoshida S, Muneyasu M (2024) Graph-based interpretability for fake news detection through topic-and propagation-aware visualization. Computation 12(4):82","journal-title":"Computation"},{"key":"2527_CR26","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.patrec.2024.02.014","volume":"180","author":"Z Zhang","year":"2024","unstructured":"Zhang Z, Lv Q, Jia X, Yun W, Miao G, Mao Z, Wu G (2024) Gbca: graph convolution network and bert combined with co-attention for fake news detection. Pattern Recogn Lett 180:26\u201332","journal-title":"Pattern Recogn Lett"},{"issue":"8","key":"2527_CR27","doi-asserted-by":"publisher","first-page":"3035","DOI":"10.1109\/TKDE.2019.2961675","volume":"33","author":"C Song","year":"2019","unstructured":"Song C, Yang C, Chen H, Tu C, Liu Z, Sun M (2019) Ced: credible early detection of social media rumors. IEEE Trans Knowl Data Eng 33(8):3035\u20133047","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2527_CR28","doi-asserted-by":"crossref","unstructured":"Zhou K, Shu C, Li B, Lau JH (2019) Early rumour detection. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 1614\u20131623","DOI":"10.18653\/v1\/N19-1163"},{"key":"2527_CR29","doi-asserted-by":"crossref","unstructured":"Shu K, Zheng G, Li Y, Mukherjee S, Awadallah AH, Ruston S, Liu H (2021) Early detection of fake news with multi-source weak social supervision. In: Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14\u201318, 2020, Proceedings, Part III, pp. 650\u2013666. Springer","DOI":"10.1007\/978-3-030-67664-3_39"},{"key":"2527_CR30","doi-asserted-by":"crossref","unstructured":"Zhang L, Zhang X, Zhou Z, Zhang X, Wang S, Yu PS, Li C (2024) Early detection of multimodal fake news via reinforced propagation path generation. IEEE Trans Knowl Data Eng","DOI":"10.1109\/TKDE.2024.3496701"},{"key":"2527_CR31","unstructured":"Rong Y, Huang W, Xu T, Huang J (2019) The truly deep graph convolutional networks for node classification. arXiv preprint arXiv:1907.109035"},{"key":"2527_CR32","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. Adv Neural Inf Process Syst, 30"},{"key":"2527_CR33","unstructured":"Monti F, Frasca F, Eynard D, Mannion D, Bronstein MM (2019) Fake news detection on social media using geometric deep learning. arXiv preprint arXiv:1902.06673"},{"key":"2527_CR34","unstructured":"Kingma DP, Ba J (2014) Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"issue":"2","key":"2527_CR35","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1007\/s00365-006-0663-2","volume":"26","author":"Y Yao","year":"2007","unstructured":"Yao Y, Rosasco L, Caponnetto A (2007) On early stopping in gradient descent learning. Constr Approx 26(2):289\u2013315","journal-title":"Constr Approx"},{"key":"2527_CR36","doi-asserted-by":"crossref","unstructured":"Zhao Z, Resnick P, Mei Q (2015) Enquiring minds: Early detection of rumors in social media from enquiry posts. In: Proceedings of the 24th International Conference on World Wide Web, pp. 1395\u20131405","DOI":"10.1145\/2736277.2741637"},{"key":"2527_CR37","doi-asserted-by":"crossref","unstructured":"Jin Z, Cao J, Zhang Y, Luo J (2016) News verification by exploiting conflicting social viewpoints in microblogs. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 30","DOI":"10.1609\/aaai.v30i1.10382"},{"key":"2527_CR38","doi-asserted-by":"crossref","unstructured":"Lu Y-J, Li C-T (2020) Gcan: Graph-aware co-attention networks for explainable fake news detection on social media. arXiv preprint arXiv:2004.11648","DOI":"10.18653\/v1\/2020.acl-main.48"},{"key":"2527_CR39","doi-asserted-by":"crossref","unstructured":"Ma J, Gao W (2020) Debunking rumors on twitter with tree transformer. In: Proceedings of the 28th International Conference on Computational Linguistics, pp. 5455\u20135466","DOI":"10.18653\/v1\/2020.coling-main.476"},{"issue":"4","key":"2527_CR40","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3391250","volume":"11","author":"J Ma","year":"2020","unstructured":"Ma J, Gao W, Joty S, Wong K-F (2020) An attention-based rumor detection model with tree-structured recursive neural networks. ACM Trans Intell Syst Technol (TIST) 11(4):1\u201328","journal-title":"ACM Trans Intell Syst Technol (TIST)"},{"key":"2527_CR41","doi-asserted-by":"crossref","unstructured":"Lin H, Ma J, Cheng M, Yang Z, Chen L, Chen G (2021) Rumor detection on twitter with claim-guided hierarchical graph attention networks. arXiv preprint arXiv:2110.04522","DOI":"10.18653\/v1\/2021.emnlp-main.786"},{"key":"2527_CR42","doi-asserted-by":"crossref","unstructured":"Mamyrbayev O, Turysbek Z, Afzal M, Abdurakhimovich MU, Galiya Y, Abdullah M, Ul\u00a0Amin R (2025) Grace: Graph-based attention for coherent explanation in fake news detection on social media. Int J Adv Comput Sci Appl, 16(1)","DOI":"10.14569\/IJACSA.2025.01601111"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-025-02527-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-025-02527-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-025-02527-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T05:44:18Z","timestamp":1763531058000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-025-02527-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,22]]},"references-count":42,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["2527"],"URL":"https:\/\/doi.org\/10.1007\/s10115-025-02527-x","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"type":"print","value":"0219-1377"},{"type":"electronic","value":"0219-3116"}],"subject":[],"published":{"date-parts":[[2025,8,22]]},"assertion":[{"value":"30 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 April 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 August 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that there is no Conflict of interest with anybody or any institution regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}