{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T13:26:43Z","timestamp":1792848403315,"version":"4.5.0"},"reference-count":59,"publisher":"Association for Computing Machinery (ACM)","issue":"8","license":[{"start":{"date-parts":[[2024,8,8]],"date-time":"2024-08-08T00:00:00Z","timestamp":1723075200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Joint Funds of the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["U22A2036"],"award-info":[{"award-number":["U22A2036"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National Key Research and Development Program of China","award":["2020YFB1406902"],"award-info":[{"award-number":["2020YFB1406902"]}]},{"name":"Key-Area Research and Development Program of Guangdong Province","award":["2020B0101360001"],"award-info":[{"award-number":["2020B0101360001"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62202123"],"award-info":[{"award-number":["62202123"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2024,8,31]]},"abstract":"<jats:p>Predicting information cascades holds significant practical implications, including applications in public opinion analysis, rumor control, and product recommendation. Existing approaches have generally overlooked the significance of semantic topics in information cascades or disregarded the dissemination relations. Such models are inadequate in capturing the intricate diffusion process within an information network inundated with diverse topics. To address such problems, we propose a neural-based model using Topic-Aware Masked Attentive Network for Information Cascade Prediction (ICP-TMAN) to predict the next infected node of an information cascade. First, we encode the topical text into user representation to perceive the user-topic dependency. Next, we employ a masked attentive network to devise the diffusion context to capture the user-context dependency. Finally, we exploit a deep attention mechanism to model historical infected nodes for user embedding enhancement to capture user-history dependency. The results of extensive experiments conducted on three real-world datasets demonstrate the superiority of ICP-TMAN over existing state-of-the-art approaches.<\/jats:p>","DOI":"10.1145\/3653449","type":"journal-article","created":{"date-parts":[[2024,3,21]],"date-time":"2024-03-21T07:52:16Z","timestamp":1711007536000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Topic-aware Masked Attentive Network for Information Cascade Prediction"],"prefix":"10.1145","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6920-9801","authenticated-orcid":false,"given":"Yu","family":"Tai","sequence":"first","affiliation":[{"name":"School of Cyberspace Science, Harbin Institute of Technology","place":["Harbin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8386-0131","authenticated-orcid":false,"given":"Hongwei","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science, Harbin Institute of Technology","place":["Harbin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6494-775X","authenticated-orcid":false,"given":"Hui","family":"He","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science, Harbin Institute of Technology","place":["Harbin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4139-052X","authenticated-orcid":false,"given":"Xinglong","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science, Harbin Institute of Technology","place":["Harbin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-3020-3494","authenticated-orcid":false,"given":"Yuanming","family":"Shao","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science, Harbin Institute of Technology","place":["Harbin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4783-876X","authenticated-orcid":false,"given":"Weizhe","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science, Harbin Institute of Technology","place":["Harbin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0229-2460","authenticated-orcid":false,"given":"Arun Kumar","family":"Sangaiah","sequence":"additional","affiliation":[{"name":"National Yunlin University of Science and Technology","place":["Beirut, Taiwan"]},{"name":"Lebanese American University","place":["Beirut, Taiwan"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,8,8]]},"reference":[{"key":"e_1_3_2_2_2","article-title":"Nonbacktracking bounds on the influence in independent cascade models","volume":"30","author":"Abbe Emmanuel","year":"2017","unstructured":"Emmanuel Abbe, Sanjeev Kulkarni, and Eun Jee Lee. 2017. Nonbacktracking bounds on the influence in independent cascade models. In Advances in Neural Information Processing Systems, Vol. 30.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-022-10191-8"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25627"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3591106.3592294"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108274"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2016.2537366"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2012.122"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118604"},{"key":"e_1_3_2_10_2","first-page":"152","volume-title":"Uncertainty in Artificial Intelligence","author":"Berenbrink Petra","year":"2023","unstructured":"Petra Berenbrink, Max Hahn-Klimroth, Dominik Kaaser, Lena Krieg, and Malin Rau. 2023. Inference of a rumor\u2019s source in the independent cascade model. In Uncertainty in Artificial Intelligence. PMLR, 152\u2013162."},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.09.017"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132973"},{"key":"e_1_3_2_13_2","first-page":"4171","volume-title":"Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT \u201919), Volume 1 (Long and Short Papers)","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT \u201919), Volume 1 (Long and Short Papers). Association for Computational Linguistics, 4171\u20134186."},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-00123-9_49"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/3301303"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1023\/A:1011122126881"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1017\/nws.2014.3"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/2086737.2086741"},{"key":"e_1_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1086\/226707"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0307752101"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/4431416"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974010.50"},{"key":"e_1_3_2_23_2","first-page":"1055","volume-title":"Proceedings of the IEEE International Conference on Data Mining (ICDM \u201918)","author":"Islam Mohammad Raihanul","year":"2018","unstructured":"Mohammad Raihanul Islam, Sathappan Muthiah, Bijaya Adhikari, B. Aditya Prakash, and Naren Ramakrishnan. 2018. DeepDiffuse: Predicting the \u2018who\u2019 and \u2018when\u2019 in cascades. In Proceedings of the IEEE International Conference on Data Mining (ICDM \u201918). IEEE Computer Society, 1055\u20131060."},{"issue":"2","key":"e_1_3_2_24_2","first-page":"1149","article-title":"A survey of community detection approaches: From statistical modeling to deep learning","volume":"35","author":"Jin Di","year":"2023","unstructured":"Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Dongxiao He, Jia Wu, Philip S. Yu, and Weixiong Zhang. 2023. A survey of community detection approaches: From statistical modeling to deep learning. IEEE Trans. Knowl. Data Eng. 35, 2 (2023), 1149\u20131170.","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956769"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557077"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1609\/icwsm.v12i1.15044"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052643"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106739"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2018.10.003"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-00123-9_35"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.1145\/3444688"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105153"},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220077"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2017.10.029"},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531730"},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20334"},{"key":"e_1_3_2_38_2","first-page":"1","article-title":"Deep attention framework for retweet prediction enriched with causal inferences","author":"Sun Wu-Jiu","year":"2023","unstructured":"Wu-Jiu Sun and Xiao Fan Liu. 2023. Deep attention framework for retweet prediction enriched with causal inferences. Appl. Intell. (2023), 1\u201321.","journal-title":"Appl. Intell."},{"key":"e_1_3_2_39_2","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1402008"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i4.20336"},{"key":"e_1_3_2_41_2","first-page":"5998","volume-title":"Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems. 5998\u20136008."},{"key":"e_1_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aml.2020.106617"},{"key":"e_1_3_2_43_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-00123-9_50"},{"key":"e_1_3_2_44_2","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482374"},{"key":"e_1_3_2_45_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2017.57"},{"key":"e_1_3_2_46_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-07174-9"},{"key":"e_1_3_2_47_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.10.029"},{"key":"e_1_3_2_48_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/416"},{"key":"e_1_3_2_49_2","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3269275"},{"key":"e_1_3_2_50_2","doi-asserted-by":"publisher","DOI":"10.5555\/3367471.3367573"},{"key":"e_1_3_2_51_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2017.05.004"},{"key":"e_1_3_2_52_2","first-page":"1","article-title":"PDA-GNN: Propagation-depth-aware graph neural networks for recommendation","author":"Wu Xinglong","year":"2023","unstructured":"Xinglong Wu, Hui He, Hongwei Yang, Yu Tai, Zejun Wang, and Weizhe Zhang. 2023. PDA-GNN: Propagation-depth-aware graph neural networks for recommendation. World Wide Web (2023), 1\u201322.","journal-title":"World Wide Web"},{"issue":"3","key":"e_1_3_2_53_2","first-page":"1128","article-title":"Neural diffusion model for microscopic cascade study","volume":"33","author":"Yang Cheng","year":"2019","unstructured":"Cheng Yang, Maosong Sun, Haoran Liu, Shiyi Han, Zhiyuan Liu, and Huanbo Luan. 2019. Neural diffusion model for microscopic cascade study. IEEE Trans. Knowl. Data Eng. 33, 3 (2019), 1128\u20131139.","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"e_1_3_2_54_2","doi-asserted-by":"publisher","DOI":"10.5555\/3367471.3367602"},{"key":"e_1_3_2_55_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-73194-6_35"},{"key":"e_1_3_2_56_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.02.090"},{"key":"e_1_3_2_57_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2022.11.163"},{"key":"e_1_3_2_58_2","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339641"},{"key":"e_1_3_2_59_2","doi-asserted-by":"publisher","DOI":"10.1145\/3433000"},{"key":"e_1_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/468"}],"container-title":["ACM Transactions on Asian and Low-Resource Language Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3653449","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3653449","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T13:24:15Z","timestamp":1752758655000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3653449"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,8]]},"references-count":59,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2024,8,31]]}},"alternative-id":["10.1145\/3653449"],"URL":"https:\/\/doi.org\/10.1145\/3653449","relation":{},"ISSN":["2375-4699","2375-4702"],"issn-type":[{"value":"2375-4699","type":"print"},{"value":"2375-4702","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,8]]},"assertion":[{"value":"2023-04-22","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-03-17","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-08-08","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}