{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T16:19:45Z","timestamp":1776183585283,"version":"3.50.1"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2021,1,11]],"date-time":"2021-01-11T00:00:00Z","timestamp":1610323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,11]],"date-time":"2021-01-11T00:00:00Z","timestamp":1610323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,4]]},"DOI":"10.1007\/s11042-020-10285-x","type":"journal-article","created":{"date-parts":[[2021,1,11]],"date-time":"2021-01-11T08:39:42Z","timestamp":1610354382000},"page":"13059-13076","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["Attention-based multimodal contextual fusion for sentiment and emotion classification using bidirectional LSTM"],"prefix":"10.1007","volume":"80","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4344-6024","authenticated-orcid":false,"given":"Mahesh G.","family":"Huddar","sequence":"first","affiliation":[]},{"given":"Sanjeev S.","family":"Sannakki","sequence":"additional","affiliation":[]},{"given":"Vijay S.","family":"Rajpurohit","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,1,11]]},"reference":[{"key":"10285_CR1","unstructured":"Bahdanau D, Cho K, Bengio Y (2014) Neural machine translation by jointly learning to align and translate, arXiv:1409.0473"},{"issue":"4","key":"10285_CR2","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1007\/s10579-008-9076-6","volume":"42","author":"C Busso","year":"2008","unstructured":"Busso C, Bulut M, Lee C, Kazemzadeh A, Mower E, Kim S, Chang J, Lee S, Narayanan S (2008) IEMOCAP: interactive emotional dyadic motion capture database. J Language Resour Evaluat 42(4):335\u2013359","journal-title":"J Language Resour Evaluat"},{"issue":"2","key":"10285_CR3","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1109\/MIS.2016.31","volume":"31","author":"E Cambria","year":"2016","unstructured":"Cambria E (2016) Affective computing and sentiment analysis. IEEE Intell Syst 31(2):102\u2013107","journal-title":"IEEE Intell Syst"},{"key":"10285_CR4","doi-asserted-by":"crossref","unstructured":"Celli F, Lepri B, Biel J-I, Gatica-Perez D, Riccardi G, Pianesi F (2014) The workshop on computational personality recognition 2014. In: Proceedings of the 22nd ACM International Conference on Multimedia. Orlando, pp 1245\u20131246","DOI":"10.1145\/2647868.2647870"},{"key":"10285_CR5","doi-asserted-by":"crossref","unstructured":"Chen LS, Huang TS, Miyasato T, Nakatsu R (1998) Multimodal human emotion\/expression recognition. In Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition, Washington, DC, pp 366\u2013371","DOI":"10.1109\/AFGR.1998.670976"},{"key":"10285_CR6","doi-asserted-by":"crossref","unstructured":"de Kok S, Punt L, van den Puttelaar R, Ranta K, Schouten K, Frasincar F (2018) Review-aggregated aspect-based sentiment analysis with ontology features. Prog Artif Intell 7(4):295\u2013306","DOI":"10.1007\/s13748-018-0163-7"},{"key":"10285_CR7","doi-asserted-by":"crossref","unstructured":"Ellis JG, Jou B, Chang S-F (2014) why we watch the news: a dataset for exploring sentiment in broadcast video news,\" in Proceedings of the 16th International Conference on Multimodal Interaction, Istanbul, Turkey","DOI":"10.1145\/2663204.2663237"},{"issue":"1\u20132","key":"10285_CR8","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1007\/s12193-009-0032-6","volume":"3","author":"F Eyben","year":"2010","unstructured":"Eyben F, W\u00f6llmer M, Graves A, Schuller B, Douglas-Cowie E, Cowie R (2010) On-line emotion recognition in a 3-D activation-valence-time continuum using acoustic and linguistic cues. J Multimodal User Interfaces 3(1\u20132):7\u201319","journal-title":"J Multimodal User Interfaces"},{"key":"10285_CR9","doi-asserted-by":"crossref","unstructured":"Eyben F, W\u00f6llmer M, Schuller B (2013) Recent developments in openSMILE, the Munich open-source multimedia feature extractor, in Proceedings of the 21st ACM international conference on Multimedia, Barcelona, Spain","DOI":"10.1145\/2502081.2502224"},{"key":"10285_CR10","doi-asserted-by":"crossref","unstructured":"Gohil S, Vuik S, Darzi A (2018) Sentiment analysis of health care tweets: review of the methods used, JMIR Public Health Surveill 4(2)","DOI":"10.2196\/publichealth.5789"},{"key":"10285_CR11","volume-title":"Speech recognition with deep recurrent neura networks, in International Conference on Acoustics","author":"A Graves","year":"2013","unstructured":"Graves A, Mohamed A-r, Hinton G (2013) Speech recognition with deep recurrent neura networks, in International Conference on Acoustics. Speech and Signal Processing, Vancouver"},{"key":"10285_CR12","doi-asserted-by":"crossref","unstructured":"Gupta P, Tiwari R, Robert N (2016) Sentiment analysis and text summarization of online reviews: a survey,\" in International Conference on Communication and Signal Processing (ICCSP), Melmaruvathur, India","DOI":"10.1109\/ICCSP.2016.7754131"},{"issue":"8","key":"10285_CR13","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780","journal-title":"Neural Comput"},{"issue":"1","key":"10285_CR14","first-page":"876","volume":"7","author":"MG Huddar","year":"2019","unstructured":"Huddar MG, Sannakki SS, Rajpurohit VS (2019) A survey of computational approaches and challenges in multimodal sentiment analysis. Int J Comput Sci Eng 7(1):876\u2013883","journal-title":"Int J Comput Sci Eng"},{"issue":"1","key":"10285_CR15","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1109\/TPAMI.2012.59","volume":"35","author":"S Ji","year":"2013","unstructured":"Ji S, Xu W, Yang M, Yu K (2013) 3d convolutional neural networks for human action recognition. IEEE Trans Pattern Anal Mach Intell 35(1):221\u2013231","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"10285_CR16","doi-asserted-by":"crossref","unstructured":"Karpathy A, Toderici G, Shetty S, Leung T, Sukthankar R, Fei-Fei L (2014) Large-scale video classification with convolutional neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, pp 1725\u20131732","DOI":"10.1109\/CVPR.2014.223"},{"key":"10285_CR17","unstructured":"Kingma DaBJ (2014) Adam: a method for stochastic optimization, arXiv preprint arXiv:1412.6980, vol 15"},{"key":"10285_CR18","doi-asserted-by":"crossref","unstructured":"Kirilenko AP, Stepchenkova SO, Kim H, Li X (2018) Automated sentiment analysis in tourism: comparison of approaches. Journal of Travel Research 57(8):1012\u20131025","DOI":"10.1177\/0047287517729757"},{"key":"10285_CR19","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1613\/jair.4272","volume":"50","author":"S Kiritchenko","year":"2014","unstructured":"Kiritchenko S, Zhu X, Mohammad SM (2014) Sentiment analysis of short informal texts. J Artif Intell Res 50:723\u2013762","journal-title":"J Artif Intell Res"},{"key":"10285_CR20","doi-asserted-by":"crossref","unstructured":"Korayem M, Crandall D, Abdul-Mageed M (2012) Subjectivity and sentiment analysis of arabic: A survey. In: International conference on advanced machine learning technologies and applications. Springer, Berlin, Heidelberg, pp 128\u2013139","DOI":"10.1007\/978-3-642-35326-0_14"},{"key":"10285_CR21","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.knosys.2014.04.022","volume":"69","author":"X Li","year":"2014","unstructured":"Li X, Xie H, iChenb L, Wang J, Deng X (2014) News impact on stock price return via sentiment analysis. Knowledge-Based Syst 69:14\u201323","journal-title":"Knowledge-Based Syst"},{"key":"10285_CR22","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1007\/978-3-031-02145-9","volume-title":"A survey of opinion mining and sentiment analysis, in mining text data","author":"B Liu","year":"2012","unstructured":"Liu B, Zhang LL (2012) A survey of opinion mining and sentiment analysis, in mining text data. Springer, Boston, pp 415\u2013463"},{"issue":"4","key":"10285_CR23","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1007\/s10462-016-9508-4","volume":"48","author":"SL Lo","year":"2017","unstructured":"Lo SL, Cambria E, Chiong R, Cornforth D (2017) Multilingual sentiment analysis: from formal to informal and scarce resource languages. Artif Intell Rev 48(4):499\u2013527","journal-title":"Artif Intell Rev"},{"issue":"3","key":"10285_CR24","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1007\/s11277-016-3346-1","volume":"89","author":"K Lyu","year":"2016","unstructured":"Lyu K, Kim H (2016) Sentiment analysis using word polarity of social media. Wirel Pers Commun 89(3):941\u2013958","journal-title":"Wirel Pers Commun"},{"key":"10285_CR25","doi-asserted-by":"crossref","unstructured":"Mariethoz J, Bengio S (2005) A unified framework for score normalization techniques applied to text-independent speaker verification. IEEE Signal Process Lett 12(7):532\u2013535","DOI":"10.1109\/LSP.2005.847860"},{"key":"10285_CR26","doi-asserted-by":"crossref","unstructured":"Mars A, Gouider MS (2017) Big data analysis to features opinions extraction of customer. Procedia Comput Sci 112:906\u2013916","DOI":"10.1016\/j.procs.2017.08.114"},{"key":"10285_CR27","unstructured":"Mikolov T, Chen K, Corrado G, Dean J (2013) Efficient Estimation of Word Representations in Vector Space,\" arXiv:1301.3781."},{"key":"10285_CR28","unstructured":"Mohammad SM, Kiritchenko S, Zhu X (2013) NRC-Canada: Building the state-of-the-art in sentiment analysis of tweets. In: Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), Atlanta, pp 321\u2013327"},{"key":"10285_CR29","volume-title":"An improved sentiment analysis of online movie reviews based on clustering for box-office prediction, in International Conference on Computing","author":"P Nagamma","year":"2015","unstructured":"Nagamma P, Pruthvi HR, Nisha KK, Shwetha NH (2015) An improved sentiment analysis of online movie reviews based on clustering for box-office prediction, in International Conference on Computing. Communication & Automation, Noida"},{"key":"10285_CR30","doi-asserted-by":"crossref","unstructured":"Nalisnick ET, Baird HS (2013) Extracting sentiment networks from Shakespeare's plays in 12th International Conference on Document Analysis and Recognition, Washington, DC, USA","DOI":"10.1109\/ICDAR.2013.155"},{"issue":"1","key":"10285_CR31","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1109\/TAFFC.2017.2713783","volume":"10","author":"F Noroozi","year":"2017","unstructured":"Noroozi F, Marjanovic M, Njegus A, Escalera S, Anbarjafari G (2017) Audio-visual emotion recognition in video clips. IEEE Trans Affect Comput 10(1):60\u201375","journal-title":"IEEE Trans Affect Comput"},{"key":"10285_CR32","doi-asserted-by":"crossref","unstructured":"Peng B, Li J, Chen J, Han X, Xu R, Wong K-F (2015) Trending sentiment-topic detection on twitter. In: International Conference on Intelligent Text Processing and Computational Linguistics. Springer, Cham, pp 66\u201377","DOI":"10.1007\/978-3-319-18117-2_5"},{"key":"10285_CR33","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1016\/j.knosys.2018.02.034","volume":"148","author":"H Penga","year":"2018","unstructured":"Penga H, Ma Y, Lib Y, Cambria E (2018) Learning multi-grained aspect target sequence for Chinese sentiment analysis. Knowl-Based Syst 148:167\u2013176","journal-title":"Knowl-Based Syst"},{"key":"10285_CR34","volume-title":"Utterance-level multimodal sentiment analysis, in Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics","author":"V Perez-Rosas","year":"2013","unstructured":"Perez-Rosas V, Mihalcea R, Morency L-P (2013) Utterance-level multimodal sentiment analysis, in Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics. Sofia, Bulgaria"},{"key":"10285_CR35","doi-asserted-by":"crossref","unstructured":"Poria S, Cambria E, Gelbukh A (2015) Deep convolutional neural network textual features and multiple kernel learning for utterance-level multimodal sentiment analysis, EMNLP, p 2539\u20132544","DOI":"10.18653\/v1\/D15-1303"},{"key":"10285_CR36","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0055","volume-title":"Convolutional MKL based multimodal emotion recognition and sentiment analysis","author":"S Poria","year":"2016","unstructured":"Poria S, Chaturvedi I, Cambria E, Hussain A (2016) Convolutional MKL based multimodal emotion recognition and sentiment analysis. IEEE 16th International Conference on Data Mining (ICDM), Barcelona"},{"key":"10285_CR37","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.inffus.2017.02.003","volume":"37","author":"S Poria","year":"2017","unstructured":"Poria S, Cambria E, Bajpai R, Hussain A (2017) A review of affective computing: from unimodal analysis to multimodal fusion. Information Fusion 37:98\u2013125","journal-title":"Information Fusion"},{"key":"10285_CR38","doi-asserted-by":"crossref","unstructured":"Poria S, Cambria E, Hazarika D, Mazumder N, Zadeh AL (2017) Context-dependent sentiment analysis in user-generated. In: Proceedings of the 55th annual meeting of the association for computational linguistics (volume 1: Long papers), Vancouver, pp 873\u2013883","DOI":"10.18653\/v1\/P17-1081"},{"key":"10285_CR39","doi-asserted-by":"publisher","DOI":"10.1109\/INVENTIVE.2016.7823280","volume-title":"Election result prediction using twitter sentiment analysis","author":"J Ramteke","year":"2016","unstructured":"Ramteke J, Shah S, Godhia D, Shaikh A (2016) Election result prediction using twitter sentiment analysis. International Conference on Inventive Computation Technologies (ICICT), Coimbatore"},{"key":"10285_CR40","doi-asserted-by":"crossref","unstructured":"Rosas VP, Mihalcea R, Morency L-P (2013) Multimodal sentiment analysis of spanish online videos. IEEE Intell Syst 28(3):38\u201345","DOI":"10.1109\/MIS.2013.9"},{"key":"10285_CR41","unstructured":"Rozgi\u0107 V, Ananthakrishnan S, Saleem S, Kumar R, Prasad R (2013) Ensemble of SVM trees for multimodal emotion recognition. In: Proceedings of The 2012 Asia Pacific Signal and Information Processing Association Annual Summit and Conference. Hollywood, pp 1\u20134"},{"key":"10285_CR42","unstructured":"Teh YW, Hinton GE (2000) Rate-coded restricted Boltzmann machines for face recognition. In: Proceedings of the 13th International Conference on Neural Information Processing Systems (NIPS'00). MIT Press, Cambridge, pp 872\u2013878"},{"key":"10285_CR43","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1016\/j.procs.2015.07.295","volume":"53","author":"P Thakora","year":"2015","unstructured":"Thakora P, Sasi DS (2015) Ontology-based sentiment analysis process for social media content. Procedia Comput Sci 53:199\u2013207","journal-title":"Procedia Comput Sci"},{"issue":"3","key":"10285_CR44","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1109\/MIS.2013.34","volume":"28","author":"M W\u00f6llmer","year":"2013","unstructured":"W\u00f6llmer M, Weninger F, Knaup T, Schuller B, Sun C, Sagae K, Morency L-P (2013) YouTube movie reviews: sentiment analysis in an audio-visual context. IEEE Intell Syst 28(3):46\u201353","journal-title":"IEEE Intell Syst"},{"issue":"1","key":"10285_CR45","first-page":"10","volume":"2","author":"CH Wu","year":"2010","unstructured":"Wu CH, Liang WB (2010) Emotion recognition of affective speech based on multiple classifiers using acoustic-prosodic information and semantic labels. IEEE Trans Affect Comput 2(1):10\u201321","journal-title":"IEEE Trans Affect Comput"},{"key":"10285_CR46","unstructured":"Xu K, Ba J, Kiros R, Cho K, Courville A, Salakhutdinov R, Zemel R, Bengio Y (2015) Show, attend and tell: Neural image caption generation with visual attention. In: International Conference on Machine Learning, Lille, pp 2048\u20132057"},{"key":"10285_CR47","doi-asserted-by":"crossref","unstructured":"Zadeh A, Zellers R, Pincus E, Morency L-P (2016) Multimodal sentiment intensity analysis in videos: facial gestures and verbal messages. IEEE Intell Syst 31(6):82\u201388","DOI":"10.1109\/MIS.2016.94"},{"key":"10285_CR48","doi-asserted-by":"crossref","unstructured":"Zadeh A, Chen M, Poria S, Cambria E, Morency L-P (2017) Tensor fusion network for multimodal sentiment analysis. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Copenhagen, pp 1103\u20131114","DOI":"10.18653\/v1\/D17-1115"}],"updated-by":[{"DOI":"10.1007\/s11042-021-10591-y","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2021,2,20]],"date-time":"2021-02-20T00:00:00Z","timestamp":1613779200000}}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-10285-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-10285-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-10285-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,11]],"date-time":"2022-12-11T06:03:29Z","timestamp":1670738609000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-10285-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,11]]},"references-count":48,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2021,4]]}},"alternative-id":["10285"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-10285-x","relation":{"correction":[{"id-type":"doi","id":"10.1007\/s11042-021-10591-y","asserted-by":"object"}]},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,11]]},"assertion":[{"value":"1 June 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 November 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 December 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 January 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 February 2021","order":5,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":6,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"A Correction to this paper has been published:","order":7,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"https:\/\/doi.org\/10.1007\/s11042-021-10591-y","URL":"https:\/\/doi.org\/10.1007\/s11042-021-10591-y","order":8,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}}]}}