{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:09:28Z","timestamp":1750219768679,"version":"3.41.0"},"reference-count":30,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T00:00:00Z","timestamp":1695859200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["J. Data and Information Quality"],"published-print":{"date-parts":[[2023,9,30]]},"abstract":"<jats:p>Academics and businesses are paying intense attention to social network alignment, which centers various social networks around their shared members. All studies to date treat the social network as static and ignore its innate dynamism. In reality, an individual's discriminative pattern is embedded in the dynamics of social networks, and this information may be used to improve social network alignment. This study finds that these dynamics can reveal more apparent patterns better suited to lining up the social web of things (SWoT). The correlation between the user structure and attributes for each social network must be maintained to combine the binary dynamics and make the original synthetic embedding representation. Finally, the initial embedding of each network is projected to a target subspace as part of the semi-supervised spatial transformation learning process. The Dynamic Social Network Alignment approach outperforms the current mainstream algorithm by 10% in this article's extensive series of trials using real-world datasets. The findings of this study show that this alignment of enormous networks addresses the volume, variety, velocity, and veracity (or 4Vs) of vast networks. To improve the efficacy and resilience of an adversarial network alignment, adversarial learning techniques can be applied. The results show that the model with structure, attribute, and time information performs the best, while the model without attribute information comes in second, the model without time information performs mediocrely, and the model without structure information performs the worst.<\/jats:p>","DOI":"10.1145\/3603711","type":"journal-article","created":{"date-parts":[[2023,6,14]],"date-time":"2023-06-14T11:26:05Z","timestamp":1686741965000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Deep Learning\u2013based Dynamic User Alignment in Social Networks"],"prefix":"10.1145","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8647-1393","authenticated-orcid":false,"given":"Khaled","family":"Matrouk","sequence":"first","affiliation":[{"name":"Computer Engineering Department, Al-Hussein Bin Talal University, Ma'an, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9435-2343","authenticated-orcid":false,"given":"Srikanth","family":"V","sequence":"additional","affiliation":[{"name":"School of CS and IT, Department of MCA, Jain (Deemed-to-be University), Bengaluru, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1554-6578","authenticated-orcid":false,"given":"Sumit","family":"Kumar","sequence":"additional","affiliation":[{"name":"Indian Institute of Management, Kozhikode, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3564-2057","authenticated-orcid":false,"given":"Mohit Kumar","family":"Bhadla","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Ahmedabad Institute of Technology, Ahmedabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7494-2808","authenticated-orcid":false,"given":"Mirza","family":"Sabirov","sequence":"additional","affiliation":[{"name":"The Department of Tax and Taxation, Tashkent Institute of Finance, Tashkent, Uzbekistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5701-4900","authenticated-orcid":false,"given":"Mohamed J.","family":"Saadh","sequence":"additional","affiliation":[{"name":"Department of Basic Sciences, Faculty of Pharmacy, Middle East University, Amman, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,9,28]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2021.3092746"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2021.3130149"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3002798"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2927274"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2958599"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3169889"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2020.3041171"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2021.3061702"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3055280"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3053245"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2021.3068369"},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2021.3052231"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2970442"},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2021.3074038"},{"key":"e_1_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2022.3140529"},{"key":"e_1_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3027337"},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.2174\/2352096515666220513111522"},{"key":"e_1_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2022.3186703"},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1812.01780"},{"key":"e_1_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3025210"},{"key":"e_1_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICSAI53574.2021.9664205"},{"key":"e_1_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13278-021-00799-z"},{"key":"e_1_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-018-6808-5"},{"key":"e_1_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.3390\/e25010172"},{"key":"e_1_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3076264"},{"key":"e_1_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-020-00793-z"},{"key":"e_1_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.1177\/0973258620974186"},{"key":"e_1_3_1_29_2","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313430"},{"key":"e_1_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1080\/03772063.2022.2061610"},{"key":"e_1_3_1_31_2","first-page":"146","article-title":"Capturing deep dynamic information for mapping users across social networks","author":"Cai C.","year":"2019","unstructured":"C. Cai, L. Li, W. Chen, and D. Zeng. 2019. Capturing deep dynamic information for mapping users across social networks. In Proceedings of the 2019 IEEE International Conference on Intelligence and Security Informatics (ISI\u201919), 146\u2013148.","journal-title":"Proceedings of the 2019 IEEE International Conference on Intelligence and Security Informatics (ISI\u201919)"}],"container-title":["Journal of Data and Information Quality"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3603711","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3603711","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:21Z","timestamp":1750178241000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3603711"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9,28]]},"references-count":30,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,9,30]]}},"alternative-id":["10.1145\/3603711"],"URL":"https:\/\/doi.org\/10.1145\/3603711","relation":{},"ISSN":["1936-1955","1936-1963"],"issn-type":[{"type":"print","value":"1936-1955"},{"type":"electronic","value":"1936-1963"}],"subject":[],"published":{"date-parts":[[2023,9,28]]},"assertion":[{"value":"2022-12-07","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-05-18","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-09-28","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}