{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T15:44:17Z","timestamp":1772207057289,"version":"3.50.1"},"reference-count":35,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Chongqing Municipal Technology Innovation and Application Demonstration Special Industry Key Research and Development Project","award":["cstc2018jszx-cyzdX0124"],"award-info":[{"award-number":["cstc2018jszx-cyzdX0124"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.3006569","type":"journal-article","created":{"date-parts":[[2020,7,2]],"date-time":"2020-07-02T20:27:41Z","timestamp":1593721661000},"page":"121014-121021","source":"Crossref","is-referenced-by-count":27,"title":["Sentiment Analysis via Deep Multichannel Neural Networks With Variational Information Bottleneck"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5739-9054","authenticated-orcid":false,"given":"Tong","family":"Gu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9923-4725","authenticated-orcid":false,"given":"Guoliang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9160-3047","authenticated-orcid":false,"given":"Jiangtao","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","first-page":"1","article-title":"Deep variational information bottleneck","author":"alemi","year":"2017","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ITW.2015.7133169"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2969205"},{"key":"ref35","first-page":"1319","article-title":"Maxout networks","author":"goodfellow","year":"2013","journal-title":"Proc Int Conf Mach Learn (ICML)"},{"key":"ref34","first-page":"1","article-title":"Auto-encoding variational Bayes","author":"kingma","year":"2014","journal-title":"Proc Int Conf Learn Represent (ICLR)"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"ref11","first-page":"2227","article-title":"Deep contextualize word representations","author":"peters","year":"2018","journal-title":"Proc Conf North Amer Chapter Assoc Comput Linguistics (NAACL)"},{"key":"ref12","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"devlin","year":"2018","journal-title":"arXiv 1810 04805"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1181"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P14-1062"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1052"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/IDAP.2018.8620751"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CCI.2016.7778967"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICBSLP.2018.8554396"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICIS46139.2019.8940289"},{"key":"ref28","first-page":"1563","article-title":"Sentiment analysis via deep hybrid textual-crowd learning model","author":"dizaji","year":"2018","journal-title":"Proc AAAI Conf Artif Intell (AAAI)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2017.23"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/AITC.2019.8920880"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2016.31"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2982538"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00218"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/IDAP.2019.8875985"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2006.18.7.1527"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICIRCA.2018.8597286"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2017.3121555"},{"key":"ref9","article-title":"Efficient estimation of word representations in vector space","author":"mikolov","year":"2013","journal-title":"arXiv 1301 3781 [cs]"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2969854"},{"key":"ref20","first-page":"2267","article-title":"Recurrent convolutional neural networks for text classification","volume":"333","author":"lai","year":"2015","journal-title":"Proc AAAI Conf Artif Intell (AAAI)"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2900335"},{"key":"ref21","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"arXiv 1706 03762"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.01.006"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.01.024"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.08.054"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2984284"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09131758.pdf?arnumber=9131758","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T01:09:35Z","timestamp":1641949775000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9131758\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/access.2020.3006569","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}