{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T15:52:30Z","timestamp":1776441150287,"version":"3.51.2"},"publisher-location":"New York, NY, USA","reference-count":46,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,18]],"date-time":"2019-07-18T00:00:00Z","timestamp":1563408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Natural Science Foundation of China","award":["Grant No. 61725203, 61722204, 61602147, 61732008, 61632007"],"award-info":[{"award-number":["Grant No. 61725203, 61722204, 61602147, 61732008, 61632007"]}]},{"name":"Anhui Provincial Natural Science Foundation","award":["1708085QF155"],"award-info":[{"award-number":["1708085QF155"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["JZ2018HGTB0230"],"award-info":[{"award-number":["JZ2018HGTB0230"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,18]]},"DOI":"10.1145\/3331184.3331214","type":"proceedings-article","created":{"date-parts":[[2019,7,19]],"date-time":"2019-07-19T13:40:26Z","timestamp":1563543626000},"page":"235-244","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":491,"title":["A Neural Influence Diffusion Model for Social Recommendation"],"prefix":"10.1145","author":[{"given":"Le","family":"Wu","sequence":"first","affiliation":[{"name":"Hefei University of Technology, Hefei, China"}]},{"given":"Peijie","family":"Sun","sequence":"additional","affiliation":[{"name":"Hefei University of Technology, Hefei, China"}]},{"given":"Yanjie","family":"Fu","sequence":"additional","affiliation":[{"name":"Missouri University of Science and Technology, Hefei, China"}]},{"given":"Richang","family":"Hong","sequence":"additional","affiliation":[{"name":"Hefei University of Technology, Hefei, China"}]},{"given":"Xiting","family":"Wang","sequence":"additional","affiliation":[{"name":"Microsoft Research, Beijing, China"}]},{"given":"Meng","family":"Wang","sequence":"additional","affiliation":[{"name":"Hefei University of Technology, Hefei, China"}]}],"member":"320","published-online":{"date-parts":[[2019,7,18]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Accessed","year":"2019","unstructured":"{n. d.}. Wikipedia explanation of social influence. https:\/\/en.wikipedia.org\/wiki\/Social_influence. Accessed Jan 10, 2019."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.99"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","unstructured":"Aris Anagnostopoulos Ravi Kumar and Mohammad Mahdian. 2008. Influence and correlation in social networks. In SIGKDD. 7--15. 10.1145\/1401890.1401897","DOI":"10.1145\/1401890.1401897"},{"key":"e_1_3_2_2_4_1","volume-title":"Fowler","author":"Bond Robert M.","year":"2012","unstructured":"Robert M. Bond, Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime E. Settle, and James H. Fowler. 2012. A 61-million-person experiment in social influence and political mobilization. Nature, Vol. 489, 7415 (2012), 295--298."},{"key":"e_1_3_2_2_5_1","unstructured":"Joan Bruna Wojciech Zaremba Arthur Szlam and Yann Lecun. 2014. Spectral networks and locally connected networks on graphs. In ICLR."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","unstructured":"Micha\u00ebl Defferrard Xavier Bresson and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. In NIPS. 3844--3852.","DOI":"10.5555\/3157382.3157527"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","unstructured":"Guibing Guo Jie Zhang and Neil Yorke-Smith. 2015. TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings. In AAAI. 123--125.","DOI":"10.5555\/2887007.2887025"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2528249"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","unstructured":"Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li and Xiuqiang He. 2017. Deepfm: a factorization-machine based neural network for ctr prediction. In IJCAI. 1725--1731.","DOI":"10.5555\/3172077.3172127"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","unstructured":"Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In NIPS. 1024--1034.","DOI":"10.5555\/3294771.3294869"},{"key":"e_1_3_2_2_11_1","first-page":"52","article-title":"Representation learning on graphs: Methods and applications","volume":"40","author":"Hamilton William L","year":"2017","unstructured":"William L Hamilton, Rex Ying, and Jure Leskovec. 2017. Representation learning on graphs: Methods and applications. TCDE, Vol. 40, 3 (2017), 52--74.","journal-title":"TCDE"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","unstructured":"Xiangnan He Lizi Liao Hanwang Zhang Liqiang Nie Xia Hu and Tat-Seng Chua. 2017. Neural collaborative filtering. In WWW. 173--182. 10.1145\/3038912.3052569","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.2307\/2393414"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.5555\/3045118.3045167"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","unstructured":"Mohsen Jamali and Martin Ester. 2010. A matrix factorization technique with trust propagation for recommendation in social networks. In RecSys. 135--142. 10.1145\/1864708.1864736","DOI":"10.1145\/1864708.1864736"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2300487"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","unstructured":"David Kempe Jon Kleinberg and \u00c9va Tardos. 2003. Maximizing the spread of influence through a social network. In SIGKDD. ACM 137--146. 10.1145\/956750.956769","DOI":"10.1145\/956750.956769"},{"key":"e_1_3_2_2_18_1","volume-title":"Kipf and Max Welling","author":"Thomas","year":"2017","unstructured":"Thomas N. Kipf and Max Welling. 2017. Semi-supervised classification with graph convolutional networks. In ICLR."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","unstructured":"Yehuda Koren. 2008. Factorization meets the neighborhood: a multifaceted collaborative filtering model. In SIGKDD. 426--434. 10.1145\/1401890.1401944","DOI":"10.1145\/1401890.1401944"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1320040111"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1109739109"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2011.2163711"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","unstructured":"Qi Liu Biao Xiang Enhong Chen Hui Xiong Fangshuang Tang and Jeffrey Xu Yu. 2014. Influence maximization over large-scale social networks: A bounded linear approach. In CIKM. ACM 171--180. 10.1145\/2661829.2662009","DOI":"10.1145\/2661829.2662009"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","unstructured":"Hao Ma Dengyong Zhou Chao Liu Michael R. Lyu and Irwin King. 2011. Recommender systems with social regularization. In WSDM. 287--296. 10.1145\/1935826.1935877","DOI":"10.1145\/1935826.1935877"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","unstructured":"Tomas Mikolov Ilya Sutskever Kai Chen Greg S. Corrado and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In NIPS. 3111--3119.","DOI":"10.5555\/2999792.2999959"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","unstructured":"Federico Monti Michael Bronstein and Xavier Bresson. 2017. Geometric matrix completion with recurrent multi-graph neural networks. In NIPS. 3697--3707.","DOI":"10.5555\/3294996.3295127"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.168"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"crossref","unstructured":"J. Z. Qiu Jian Tang Hao Ma Y. X. Dong K. S. Wang and J. Tang. 2018. DeepInf: Modeling influence locality in large social networks. In SIGKDD. 2110--2119.","DOI":"10.1145\/3219819.3220077"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","unstructured":"Steffen Rendle. 2010. Factorization machines. In ICDM. 995--1000. 10.1109\/ICDM.2010.127","DOI":"10.1109\/ICDM.2010.127"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/2168752.2168771"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.5555\/1795114.1795167"},{"key":"e_1_3_2_2_33_1","unstructured":"Karen Simonyan and Andrew Zisserman. 2015. Very deep convolutional networks for large-scale image recognition. In ICLR."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","unstructured":"Peijie Sun Le Wu and Meng Wang. 2018. Attentive Recurrent Social Recommendation. In SIGIR. 185--194. 10.1145\/3209978.3210023","DOI":"10.1145\/3209978.3210023"},{"key":"e_1_3_2_2_35_1","first-page":"1113","article-title":"Social recommendation: a review","volume":"3","author":"Tang Jiliang","year":"2013","unstructured":"Jiliang Tang, Xia Hu, and Huan Liu. 2013. Social recommendation: a review. SNAM, Vol. 3, 4 (2013), 1113--1133.","journal-title":"SNAM"},{"key":"e_1_3_2_2_36_1","volume-title":"Graph Convolutional Matrix Completion. ICLR","author":"van den Berg Rianne","year":"2017","unstructured":"Rianne van den Berg, Thomas N. Kipf, and Max Welling. 2017. Graph Convolutional Matrix Completion. ICLR (2017)."},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","unstructured":"Hao Wang Naiyan Wang and Dit-Yan Yeung. 2015. Collaborative deep learning for recommender systems. In SIGKDD. ACM 1235--1244. 10.1145\/2783258.2783273","DOI":"10.1145\/2783258.2783273"},{"key":"e_1_3_2_2_38_1","volume-title":"A Hierarchical Attention Model for Social Contextual Image Recommendation. TKDE","author":"Wu Le","year":"2019","unstructured":"Le Wu, Lei Chen, Richang Hong, Yanjie Fu, Xing Xie, and Meng Wang. 2019. A Hierarchical Attention Model for Social Contextual Image Recommendation. TKDE (2019)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2663422"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","unstructured":"Le Wu Yong Ge Qi Liu Enhong Chen Bai Long and Zhenya Huang. 2016. Modeling Users' Preferences and Social Links in Social Networking Services: a Joint-Evolving Perspective. In AAAI. 279--286.","DOI":"10.5555\/3015812.3015853"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/2700496"},{"key":"e_1_3_2_2_42_1","volume-title":"Collaborative Neural Social Recommendation","author":"Wu Le","year":"2019","unstructured":"Le Wu, Peijie Sun, Richang Hong, Yong Ge, and Meng Wang. 2019. Collaborative Neural Social Recommendation. TSMC: Systems (2019)."},{"key":"e_1_3_2_2_43_1","unstructured":"Yuexin Wu Hanxiao Liu and Yiming Yang. 2018. Graph Convolutional Matrix Completion for Bipartite Edge Prediction. In KDIR. 51--60."},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","unstructured":"Rex Ying Ruining He Kaifeng Chen Pong Eksombatchai William L Hamilton and Jure Leskovec. 2018. Graph Convolutional Neural Networks for Web-Scale Recommender Systems. In SIGKDD. 974--983. 10.1145\/3219819.3219890","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","unstructured":"Tong Zhao Julian McAuley and Irwin King. 2014. Leveraging social connections to improve personalized ranking for collaborative filtering. In CIKM. 261--270. 10.1145\/2661829.2661998","DOI":"10.1145\/2661829.2661998"},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","unstructured":"Lei Zheng Chun-Ta Lu Fei Jiang Jiawei Zhang and Philip S Yu. 2018. Spectral collaborative filtering. In RecSys. 311--319. 10.1145\/3240323.3240343","DOI":"10.1145\/3240323.3240343"}],"event":{"name":"SIGIR '19: The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Paris France","acronym":"SIGIR '19","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3331184.3331214","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3331184.3331214","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T00:47:54Z","timestamp":1768524474000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3331184.3331214"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,18]]},"references-count":46,"alternative-id":["10.1145\/3331184.3331214","10.1145\/3331184"],"URL":"https:\/\/doi.org\/10.1145\/3331184.3331214","relation":{},"subject":[],"published":{"date-parts":[[2019,7,18]]},"assertion":[{"value":"2019-07-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}