{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T05:55:55Z","timestamp":1767851755527,"version":"3.49.0"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T00:00:00Z","timestamp":1676851200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T00:00:00Z","timestamp":1676851200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1007\/s11063-023-11181-9","type":"journal-article","created":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T17:10:33Z","timestamp":1677172233000},"page":"8869-8886","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A Contrastive Learning Framework with Tree-LSTMs for Aspect-Based Sentiment Analysis"],"prefix":"10.1007","volume":"55","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1618-7765","authenticated-orcid":false,"given":"Qichen","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Shuai","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jingmei","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,20]]},"reference":[{"issue":"1","key":"11181_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-031-02145-9","volume":"5","author":"B Liu","year":"2012","unstructured":"Liu B (2012) Sentiment analysis and opinion mining. Synthesis Lect Human Lang Technol 5(1):1\u2013167","journal-title":"Synthesis Lect Human Lang Technol"},{"key":"11181_CR2","doi-asserted-by":"crossref","unstructured":"Russo I, Caselli T, Strapparava C (2015) Semeval-2015 task 9: clipeval implicit polarity of events. In: Proceedings of the 9th international workshop on semantic evaluation (SemEval 2015), pp. 443\u2013450","DOI":"10.18653\/v1\/S15-2077"},{"key":"11181_CR3","first-page":"27","volume":"2014","author":"M Pontiki","year":"2014","unstructured":"Pontiki M, Papageorgiou H, Galanis D, Androutsopoulos I, Pavlopoulos J, Manandhar S (2014) Semeval-2014 task 4: aspect based sentiment analysis. SemEval 2014:27","journal-title":"SemEval"},{"key":"11181_CR4","unstructured":"Gu S, Zhang L, Hou Y, Song Y (2018) A position-aware bidirectional attention network for aspect-level sentiment analysis. In: Proceedings of the 27th international conference on computational linguistics, pp. 774\u2013784"},{"key":"11181_CR5","doi-asserted-by":"crossref","unstructured":"Huang B, Ou Y, Carley KM (2018) Aspect level sentiment classification with attention-over-attention neural networks. In: International conference on social computing, behavioral-cultural modeling and prediction and behavior representation in modeling and simulation, pp. 197\u2013206. Springer","DOI":"10.1007\/978-3-319-93372-6_22"},{"key":"11181_CR6","doi-asserted-by":"crossref","unstructured":"Wang K, Shen W, Yang Y, Quan X, Wang R (2020) Relational graph attention network for aspect-based sentiment analysis. In: Proceedings of the 58th annual meeting of the association for computational linguistics, pp. 3229\u20133238","DOI":"10.18653\/v1\/2020.acl-main.295"},{"key":"11181_CR7","doi-asserted-by":"crossref","unstructured":"Pang S, Xue Y, Yan Z, Huang W, Feng J (2021) Dynamic and multi-channel graph convolutional networks for aspect-based sentiment analysis. In: Findings of the association for computational linguistics: ACL-IJCNLP 2021, pp. 2627\u20132636","DOI":"10.18653\/v1\/2021.findings-acl.232"},{"key":"11181_CR8","doi-asserted-by":"crossref","unstructured":"Li R, Chen H, Feng F, Ma Z, Wang X, Hovy E (2021) Dual graph convolutional networks for aspect-based sentiment analysis. In: Proceedings of the 59th annual meeting of the association for computational linguistics and the 11th international joint conference on natural language processing (Volume 1: Long Papers), pp. 6319\u20136329","DOI":"10.18653\/v1\/2021.acl-long.494"},{"key":"11181_CR9","doi-asserted-by":"crossref","unstructured":"Liang S, Wei W, Mao X-L, Wang F, He Z (2022) Bisyn-gat+: Bi-syntax aware graph attention network for aspect-based sentiment analysis. In: Findings of the association for computational linguistics: ACL 2022, pp. 1835\u20131848","DOI":"10.18653\/v1\/2022.findings-acl.144"},{"key":"11181_CR10","doi-asserted-by":"crossref","unstructured":"Zhang K, Zhang K, Zhang M, Zhao H, Liu Q, Wu W, Chen E (2022) Incorporating dynamic semantics into pre-trained language model for aspect-based sentiment analysis. In: Findings of the association for computational linguistics: ACL 2022, pp. 3599\u20133610","DOI":"10.18653\/v1\/2022.findings-acl.285"},{"key":"11181_CR11","doi-asserted-by":"publisher","first-page":"107220","DOI":"10.1016\/j.knosys.2021.107220","volume":"227","author":"A Zhao","year":"2021","unstructured":"Zhao A, Yu Y (2021) Knowledge-enabled bert for aspect-based sentiment analysis. Knowl-Based Sys 227:107220","journal-title":"Knowl-Based Sys"},{"key":"11181_CR12","doi-asserted-by":"crossref","unstructured":"He R, Lee WS, Ng HT, Dahlmeier D (2018) Exploiting document knowledge for aspect-level sentiment classification. In: Proceedings of the 56th annual meeting of the association for computational linguistics (Volume 2: Short Papers), pp. 579\u2013585","DOI":"10.18653\/v1\/P18-2092"},{"key":"11181_CR13","doi-asserted-by":"crossref","unstructured":"Zhang Y, Zhang M, Wu S, Zhao J (2022) Towards unifying the label space for aspect-and sentence-based sentiment analysis. In: Findings of the association for computational linguistics: ACL 2022, pp. 20\u201330","DOI":"10.18653\/v1\/2022.findings-acl.3"},{"key":"11181_CR14","doi-asserted-by":"crossref","unstructured":"Jiang Q, Chen L, Xu R, Ao X, Yang M (2019) A challenge dataset and effective models for aspect-based sentiment analysis. In: Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP), pp. 6280\u20136285","DOI":"10.18653\/v1\/D19-1654"},{"key":"11181_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-022-01535-5","author":"G Li","year":"2022","unstructured":"Li G, Wang H, Ding Y, Zhou K, Yan X (2022) Data augmentation for aspect-based sentiment analysis. Int J Mach Learn Cybern. https:\/\/doi.org\/10.1007\/s13042-022-01535-5","journal-title":"Int J Mach Learn Cybern"},{"key":"11181_CR16","doi-asserted-by":"crossref","unstructured":"Tai KS, Socher R, Manning CD (2015) Improved semantic representations from tree-structured long short-term memory networks. arXiv preprint arXiv:1503.00075","DOI":"10.3115\/v1\/P15-1150"},{"key":"11181_CR17","first-page":"1","volume":"21","author":"C Raffel","year":"2020","unstructured":"Raffel C, Shazeer N, Roberts A, Lee K, Narang S, Matena M, Zhou Y, Li W, Liu PJ (2020) Exploring the limits of transfer learning with a unified text-to-text transformer. J Mach Learn Res 21:1\u201367","journal-title":"J Mach Learn Res"},{"key":"11181_CR18","doi-asserted-by":"crossref","unstructured":"Dong L, Wei F, Tan C, Tang D, Zhou M, Xu K (2014) Adaptive recursive neural network for target-dependent twitter sentiment classification. In: Proceedings of the 52nd annual meeting of the association for computational linguistics (volume 2: Short Papers), pp. 49\u201354","DOI":"10.3115\/v1\/P14-2009"},{"issue":"4","key":"11181_CR19","first-page":"1253","volume":"8","author":"L Zhang","year":"2018","unstructured":"Zhang L, Wang S, Liu B (2018) Deep learning for sentiment analysis: a survey. Wiley Interdisc Rev: Data Min Knowl Discov 8(4):1253","journal-title":"Wiley Interdisc Rev: Data Min Knowl Discov"},{"key":"11181_CR20","doi-asserted-by":"crossref","unstructured":"Wei W, Liu J, Mao X, Guo G, Zhu F, Zhou P, Hu Y (2019) Emotion-aware chat machine: Automatic emotional response generation for human-like emotional interaction. In: Proceedings of the 28th ACM international conference on information and knowledge management, pp. 1401\u20131410","DOI":"10.1145\/3357384.3357937"},{"issue":"1","key":"11181_CR21","first-page":"1","volume":"39","author":"T Lan","year":"2020","unstructured":"Lan T, Mao X-L, Wei W, Gao X, Huang H (2020) Pone: a novel automatic evaluation metric for open-domain generative dialogue systems. ACM Trans Inf Sys (TOIS) 39(1):1\u201337","journal-title":"ACM Trans Inf Sys (TOIS)"},{"key":"11181_CR22","doi-asserted-by":"crossref","unstructured":"Qiu M, Huang X, Chen C, Ji F, Qu C, Wei W, Huang J, Zhang Y (2021) Reinforced history backtracking for conversational question answering. In: Thirty-Fifth AAAI conference on artificial intelligence, AAAI, pp. 13718\u201313726","DOI":"10.1609\/aaai.v35i15.17617"},{"key":"11181_CR23","doi-asserted-by":"crossref","unstructured":"Musto C, de Gemmis M, Semeraro G, Lops P (2017) A multi-criteria recommender system exploiting aspect-based sentiment analysis of users\u2019 reviews. In: Proceedings of the eleventh ACM conference on recommender systems, pp. 321\u2013325","DOI":"10.1145\/3109859.3109905"},{"issue":"2","key":"11181_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3432049","volume":"39","author":"P Liu","year":"2021","unstructured":"Liu P, Zhang L, Gulla JA (2021) Multilingual review-aware deep recommender system via aspect-based sentiment analysis. ACM Trans Inf Sys (TOIS) 39(2):1\u201333","journal-title":"ACM Trans Inf Sys (TOIS)"},{"key":"11181_CR25","doi-asserted-by":"publisher","first-page":"107134","DOI":"10.1016\/j.knosys.2021.107134","volume":"226","author":"M Birjali","year":"2021","unstructured":"Birjali M, Kasri M, Beni-Hssane A (2021) A comprehensive survey on sentiment analysis: approaches, challenges and trends. Knowl-Based Sys 226:107134","journal-title":"Knowl-Based Sys"},{"issue":"7","key":"11181_CR26","doi-asserted-by":"publisher","first-page":"5731","DOI":"10.1007\/s10462-022-10144-1","volume":"55","author":"M Wankhade","year":"2022","unstructured":"Wankhade M, Rao ACS, Kulkarni C (2022) A survey on sentiment analysis methods, applications, and challenges. Artif Intell Rev 55(7):5731\u20135780","journal-title":"Artif Intell Rev"},{"key":"11181_CR27","doi-asserted-by":"crossref","unstructured":"Wang Y, Huang M, Zhu X, Zhao L (2016) Attention-based lstm for aspect-level sentiment classification. In: Proceedings of the 2016 conference on empirical methods in natural language processing, pp. 606\u2013615","DOI":"10.18653\/v1\/D16-1058"},{"key":"11181_CR28","doi-asserted-by":"crossref","unstructured":"Chen P, Sun Z, Bing L, Yang W (2017) Recurrent attention network on memory for aspect sentiment analysis. In: Proceedings of the 2017 Conference on empirical methods in natural language processing, pp. 452\u2013461","DOI":"10.18653\/v1\/D17-1047"},{"key":"11181_CR29","doi-asserted-by":"crossref","unstructured":"Zhang C, Li Q, Song D (2019) Aspect-based sentiment classification with aspect-specific graph convolutional networks. In: Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP), pp. 4568\u20134578","DOI":"10.18653\/v1\/D19-1464"},{"key":"11181_CR30","doi-asserted-by":"crossref","unstructured":"Sun K, Zhang R, Mensah S, Mao Y, Liu X (2019) Aspect-level sentiment analysis via convolution over dependency tree. In: Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP), pp. 5679\u20135688","DOI":"10.18653\/v1\/D19-1569"},{"key":"11181_CR31","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. Adv Neur Inf Process Sys, 30"},{"key":"11181_CR32","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1109\/TASLP.2020.3042009","volume":"29","author":"X Bai","year":"2020","unstructured":"Bai X, Liu P, Zhang Y (2020) Investigating typed syntactic dependencies for targeted sentiment classification using graph attention neural network. IEEE\/ACM Trans Audio, Speech, Lang Process 29:503\u2013514","journal-title":"IEEE\/ACM Trans Audio, Speech, Lang Process"},{"key":"11181_CR33","doi-asserted-by":"crossref","unstructured":"Yu J, Gong C, Xia R (2021) Cross-domain review generation for aspect-based sentiment analysis. In: Findings of the association for computational linguistics: ACL-IJCNLP 2021, pp. 4767\u20134777","DOI":"10.18653\/v1\/2021.findings-acl.421"},{"key":"11181_CR34","doi-asserted-by":"crossref","unstructured":"Chen Z, Qian T (2019) Transfer capsule network for aspect level sentiment classification. In: Proceedings of the 57th Annual meeting of the association for computational linguistics, pp. 547\u2013556","DOI":"10.18653\/v1\/P19-1052"},{"key":"11181_CR35","doi-asserted-by":"crossref","unstructured":"Liang Y, Meng F, Zhang J, Xu J, Chen Y, Zhou J (2020) An iterative knowledge transfer network with routing for aspect-based sentiment analysis. arXiv preprint arXiv:2004.01935","DOI":"10.18653\/v1\/2021.findings-emnlp.152"},{"key":"11181_CR36","doi-asserted-by":"crossref","unstructured":"Yu G, Ao X, Luo L, Yang M, Sun X, Li J, He Q (2021) Making flexible use of subtasks: A multiplex interaction network for unified aspect-based sentiment analysis. In: Findings of the association for computational linguistics: ACL-IJCNLP 2021, pp. 2695\u20132705","DOI":"10.18653\/v1\/2021.findings-acl.238"},{"key":"11181_CR37","unstructured":"Wang B, Ding L, Zhong Q, Li X, Tao D (2022) A contrastive cross-channel data augmentation framework for aspect-based sentiment analysis. arXiv preprint arXiv:2204.07832"},{"key":"11181_CR38","unstructured":"Devlin J, Chang M-W, Lee K, Toutanova K (2018) Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805"},{"key":"11181_CR39","doi-asserted-by":"crossref","unstructured":"Song Y, Wang J, Jiang T, Liu Z, Rao Y (2019) Attentional encoder network for targeted sentiment classification. arXiv preprint arXiv:1902.09314","DOI":"10.1007\/978-3-030-30490-4_9"},{"key":"11181_CR40","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"11181_CR41","unstructured":"Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"key":"11181_CR42","doi-asserted-by":"crossref","unstructured":"Fan F, Feng Y, Zhao D (2018) Multi-grained attention network for aspect-level sentiment classification. In: Proceedings of the 2018 conference on empirical methods in natural language processing, pp. 3433\u20133442","DOI":"10.18653\/v1\/D18-1380"},{"key":"11181_CR43","doi-asserted-by":"crossref","unstructured":"Zhang M, Qian T (2020) Convolution over hierarchical syntactic and lexical graphs for aspect level sentiment analysis. In: Proceedings of the 2020 conference on empirical methods in natural language processing (EMNLP), pp. 3540\u20133549","DOI":"10.18653\/v1\/2020.emnlp-main.286"},{"key":"11181_CR44","doi-asserted-by":"crossref","unstructured":"Tang H, Ji D, Li C, Zhou Q (2020) Dependency graph enhanced dual-transformer structure for aspect-based sentiment classification. In: Proceedings of the 58th annual meeting of the association for computational linguistics, pp. 6578\u20136588","DOI":"10.18653\/v1\/2020.acl-main.588"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-023-11181-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11063-023-11181-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-023-11181-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,11]],"date-time":"2023-11-11T17:05:40Z","timestamp":1699722340000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11063-023-11181-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,20]]},"references-count":44,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2023,12]]}},"alternative-id":["11181"],"URL":"https:\/\/doi.org\/10.1007\/s11063-023-11181-9","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"value":"1370-4621","type":"print"},{"value":"1573-773X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,20]]},"assertion":[{"value":"1 February 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 February 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No conflict of interest exits in the submission of this manuscript, and manuscript is approved by all authors for publication. I would like to declare on behalf of my co-authors that the work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part. All the authors listed have approved the manuscript that is enclosed.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}