{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T08:38:45Z","timestamp":1770971925679,"version":"3.50.1"},"reference-count":71,"publisher":"Springer Science and Business Media LLC","issue":"23","license":[{"start":{"date-parts":[[2020,4,23]],"date-time":"2020-04-23T00:00:00Z","timestamp":1587600000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,4,23]],"date-time":"2020-04-23T00:00:00Z","timestamp":1587600000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","award":["201508390019"],"award-info":[{"award-number":["201508390019"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2020,12]]},"DOI":"10.1007\/s00521-020-04937-0","type":"journal-article","created":{"date-parts":[[2020,4,23]],"date-time":"2020-04-23T05:02:36Z","timestamp":1587618156000},"page":"17601-17622","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Electronic word-of-mouth effects on studio performance leveraging attention-based model"],"prefix":"10.1007","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9410-1755","authenticated-orcid":false,"given":"Yang","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Fei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingguo","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bobo","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lili","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Donghong","family":"Ji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joaqu\u00edn","family":"Ordieres Mer\u00e9","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,4,23]]},"reference":[{"key":"4937_CR1","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1016\/j.ipm.2016.07.001","volume":"53","author":"R Piryani","year":"2017","unstructured":"Piryani R, Madhavi D, Singh VK (2017) Analytical mapping of opinion mining and sentiment analysis research during 2000\u20132015. Inf Process Manag 53:122\u2013150. https:\/\/doi.org\/10.1016\/j.ipm.2016.07.001","journal-title":"Inf Process Manag"},{"key":"4937_CR2","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.cosrev.2017.10.002","volume":"27","author":"MV M\u00e4ntyl\u00e4","year":"2018","unstructured":"M\u00e4ntyl\u00e4 MV, Graziotin D, Kuutila M (2018) The evolution of sentiment analysis\u2014a review of research topics, venues, and top cited papers. Comput Sci Rev 27:16\u201332. https:\/\/doi.org\/10.1016\/j.cosrev.2017.10.002","journal-title":"Comput Sci Rev"},{"key":"4937_CR3","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.jcps.2011.04.002","volume":"21","author":"AE Schlosser","year":"2011","unstructured":"Schlosser AE (2011) Can including pros and cons increase the helpfulness and persuasiveness of online reviews? The interactive effects of ratings and arguments. J Consum Psychol 21:226\u2013239. https:\/\/doi.org\/10.1016\/j.jcps.2011.04.002","journal-title":"J Consum Psychol"},{"key":"4937_CR4","doi-asserted-by":"publisher","first-page":"47","DOI":"10.2501\/IJA-30-1-047-075","volume":"30","author":"S-C Chu","year":"2011","unstructured":"Chu S-C, Kim Y (2011) Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. Inte J Advert 30:47\u201375. https:\/\/doi.org\/10.2501\/IJA-30-1-047-075","journal-title":"Inte J Advert"},{"key":"4937_CR5","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1007\/978-3-211-77280-5_4","volume-title":"Information and communication technologies in tourism 2008","author":"U Gretzel","year":"2008","unstructured":"Gretzel U, Yoo KH (2008) Use and impact of online travel reviews. In: O\u2019Connor P, H\u00f6pken W, Gretzel U (eds) Information and communication technologies in tourism 2008. Springer, Vienna, pp 35\u201346"},{"key":"4937_CR6","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.jbusres.2007.11.017","volume":"62","author":"C Park","year":"2009","unstructured":"Park C, Lee TM (2009) Information direction, website reputation and eWOM effect: a moderating role of product type. J Bus Res 62:61\u201367. https:\/\/doi.org\/10.1016\/j.jbusres.2007.11.017","journal-title":"J Bus Res"},{"key":"4937_CR7","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1016\/j.jretai.2008.04.005","volume":"84","author":"W Duan","year":"2008","unstructured":"Duan W, Gu B, Whinston A (2008) The dynamics of online word-of-mouth and product sales\u2014an empirical investigation of the movie industry. J Retail 84:233\u2013242. https:\/\/doi.org\/10.1016\/j.jretai.2008.04.005","journal-title":"J Retail"},{"key":"4937_CR8","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1509\/jmkg.70.3.74","volume":"70","author":"Y Liu","year":"2006","unstructured":"Liu Y (2006) Word of mouth for movies: its dynamics and impact on box office revenue. J Mark 70:74\u201389. https:\/\/doi.org\/10.1509\/jmkg.70.3.74","journal-title":"J Mark"},{"issue":"2","key":"4937_CR9","first-page":"93","volume":"10","author":"YC Kao","year":"2015","unstructured":"Kao YC, Shyu J, Huang JY (2015) eWOM for stock market by big data methods. J Acc Finance Manage Strategy 10(2):93\u2013106","journal-title":"J Acc Finance Manage Strategy"},{"key":"4937_CR10","doi-asserted-by":"publisher","first-page":"213","DOI":"10.2753\/MIS0742-1222300208","volume":"30","author":"X Luo","year":"2013","unstructured":"Luo X, Zhang J (2013) How do consumer buzz and traffic in social media marketing predict the value of the firm? J Manag Inf Syst 30:213\u2013238. https:\/\/doi.org\/10.2753\/MIS0742-1222300208","journal-title":"J Manag Inf Syst"},{"key":"4937_CR11","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1177\/0256090916650952","volume":"41","author":"A Mishra","year":"2016","unstructured":"Mishra A, Satish SM (2016) eWOM: extant research review and future research avenues. Vikalpa 41:222\u2013233. https:\/\/doi.org\/10.1177\/0256090916650952","journal-title":"Vikalpa"},{"key":"4937_CR12","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei DM (2003) Latent dirichlet allocation. J Mach Learn Res 3:993\u20131022","journal-title":"J Mach Learn Res"},{"key":"4937_CR13","first-page":"556","volume":"2001","author":"DD Lee","year":"2000","unstructured":"Lee DD, Seung HS (2000) Algorithms for non-negative matrix factorization. Adv Neural Inf Process Syst 2001:556\u2013562","journal-title":"Adv Neural Inf Process Syst"},{"key":"4937_CR14","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521:436\u2013444. https:\/\/doi.org\/10.1038\/nature14539","journal-title":"Nature"},{"key":"4937_CR15","doi-asserted-by":"crossref","unstructured":"Greene S, Resnik P (2009) More than words: syntactic packaging and implicit sentiment. Association for Computational Linguistics, Boulder, Colorado, p 503","DOI":"10.3115\/1620754.1620827"},{"key":"4937_CR16","unstructured":"Bahdanau D, Cho K, Bengio Y (2014) Neural machine translation by jointly learning to align and translate. arXiv:14090473[cs,stat]"},{"key":"4937_CR17","unstructured":"Chaudhari S, Polatkan G, Ramanath R, Mithal V (2019) An attentive survey of attention models. arXiv:190402874[cs,stat]"},{"key":"4937_CR18","first-page":"1650","volume-title":"Neural sentiment classification with user and product attention","author":"H Chen","year":"2016","unstructured":"Chen H, Sun M, Tu C et al (2016) Neural sentiment classification with user and product attention. Association for Computational Linguistics, Austin, pp 1650\u20131659"},{"key":"4937_CR19","doi-asserted-by":"crossref","unstructured":"Yang Z, Yang D, Dyer C et al (2016) Hierarchical attention networks for document classification. Association for Computational Linguistics, pp 1480\u20131489","DOI":"10.18653\/v1\/N16-1174"},{"key":"4937_CR20","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1162\/tacl_a_00097","volume":"4","author":"W Yin","year":"2016","unstructured":"Yin W, Sch\u00fctze H, Xiang B, Zhou B (2016) ABCNN: attention-based convolutional neural network for modeling sentence pairs. Trans Assoc Comput Linguist 4:259\u2013272. https:\/\/doi.org\/10.1162\/tacl_a_00097","journal-title":"Trans Assoc Comput Linguist"},{"key":"4937_CR21","first-page":"606","volume-title":"Attention-based LSTM for aspect-level sentiment classification","author":"Y Wang","year":"2016","unstructured":"Wang Y, Huang M, Xiaoyan Z, Zhao L (2016) Attention-based LSTM for aspect-level sentiment classification. Association for Computational Linguistics, Austin, pp 606\u2013615"},{"key":"4937_CR22","doi-asserted-by":"crossref","unstructured":"Wu Z, Dai X-Y, Yin C et al (2018) Improving review representations with user attention and product attention for sentiment classification. arXiv:180107861[cs]","DOI":"10.1609\/aaai.v32i1.12054"},{"key":"4937_CR23","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.620821","author":"CN Dellarocas","year":"2004","unstructured":"Dellarocas CN, Awad N, Zhang X (2004) Using online reviews as a proxy of word-of-mouth for motion picture revenue forecasting. SSRN Electron J. https:\/\/doi.org\/10.2139\/ssrn.620821","journal-title":"SSRN Electron J"},{"key":"4937_CR24","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/j.intmar.2010.04.001","volume":"24","author":"A Chakravarty","year":"2010","unstructured":"Chakravarty A, Liu Y, Mazumdar T (2010) The differential effects of online word-of-mouth and critics\u2019 reviews on pre-release movie evaluation. J Interact Mark 24:185\u2013197. https:\/\/doi.org\/10.1016\/j.intmar.2010.04.001","journal-title":"J Interact Mark"},{"key":"4937_CR25","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1080\/08997764.2013.785551","volume":"26","author":"SH Kim","year":"2013","unstructured":"Kim SH, Park N, Park SH (2013) Exploring the effects of online word of mouth and expert reviews on theatrical movies\u2019 box office success. J Media Econ 26:98\u2013114. https:\/\/doi.org\/10.1080\/08997764.2013.785551","journal-title":"J Media Econ"},{"key":"4937_CR26","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/j.jart.2015.02.001","volume":"13","author":"R Ullah","year":"2015","unstructured":"Ullah R, Zeb A, Kim W (2015) The impact of emotions on the helpfulness of movie reviews. J Appl Res Technol 13:359\u2013363. https:\/\/doi.org\/10.1016\/j.jart.2015.02.001","journal-title":"J Appl Res Technol"},{"key":"4937_CR27","doi-asserted-by":"publisher","first-page":"608","DOI":"10.1016\/j.ins.2016.08.027","volume":"372","author":"M Hur","year":"2016","unstructured":"Hur M, Kang P, Cho S (2016) Box-office forecasting based on sentiments of movie reviews and Independent subspace method. Inf Sci 372:608\u2013624. https:\/\/doi.org\/10.1016\/j.ins.2016.08.027","journal-title":"Inf Sci"},{"key":"4937_CR28","doi-asserted-by":"publisher","first-page":"874","DOI":"10.1080\/07421222.2016.1243969","volume":"33","author":"MT Lash","year":"2016","unstructured":"Lash MT, Zhao K (2016) Early predictions of movie success: the who, what, and when of profitability. J Manag Inf Syst 33:874\u2013903. https:\/\/doi.org\/10.1080\/07421222.2016.1243969","journal-title":"J Manag Inf Syst"},{"key":"4937_CR29","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1016\/j.elerap.2017.03.001","volume":"22","author":"JH Lee","year":"2017","unstructured":"Lee JH, Jung SH, Park J (2017) The role of entropy of review text sentiments on online WOM and movie box office sales. Electron Commer Res Appl 22:42\u201352. https:\/\/doi.org\/10.1016\/j.elerap.2017.03.001","journal-title":"Electron Commer Res Appl"},{"key":"4937_CR30","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.elerap.2017.02.001","volume":"22","author":"H Baek","year":"2017","unstructured":"Baek H, Oh S, Yang H-D, Ahn J (2017) Electronic word-of-mouth, box office revenue and social media. Electron Commer Res Appl 22:13\u201323. https:\/\/doi.org\/10.1016\/j.elerap.2017.02.001","journal-title":"Electron Commer Res Appl"},{"key":"4937_CR31","doi-asserted-by":"publisher","first-page":"1014","DOI":"10.1108\/IntR-07-2016-0223","volume":"27","author":"J Xun","year":"2017","unstructured":"Xun J, Guo B (2017) Twitter as customer\u2019s eWOM: an empirical study on their impact on firm financial performance. Int Res 27:1014\u20131038. https:\/\/doi.org\/10.1108\/IntR-07-2016-0223","journal-title":"Int Res"},{"key":"4937_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijresmar.2019.01.010","author":"SAM Vermeer","year":"2019","unstructured":"Vermeer SAM, Araujo T, Bernritter SF, van Noort G (2019) Seeing the wood for the trees: how machine learning can help firms in identifying relevant electronic word-of-mouth in social media. Int J Res Mark. https:\/\/doi.org\/10.1016\/j.ijresmar.2019.01.010","journal-title":"Int J Res Mark"},{"key":"4937_CR33","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.tourman.2008.04.003","volume":"30","author":"T Kim","year":"2009","unstructured":"Kim T, Kim WG, Kim HB (2009) The effects of perceived justice on recovery satisfaction, trust, word-of-mouth, and revisit intention in upscale hotels. Tour Manag 30:51\u201362. https:\/\/doi.org\/10.1016\/j.tourman.2008.04.003","journal-title":"Tour Manag"},{"key":"4937_CR34","doi-asserted-by":"publisher","first-page":"539","DOI":"10.25300\/MISQ\/2014\/38.2.10","volume":"38","author":"D Yin","year":"2014","unstructured":"Yin D, Bond SD, Georgia Institute of Technology et al (2014) Anxious or angry? Effects of discrete emotions on the perceived helpfulness of online reviews. MIS Q 38:539\u2013560. https:\/\/doi.org\/10.25300\/MISQ\/2014\/38.2.10","journal-title":"MIS Q"},{"issue":"3","key":"4937_CR35","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1509\/jmkg.71.3.075","volume":"71","author":"X Luo","year":"2007","unstructured":"Luo X (2007) Consumer negative voice and firm-idiosyncratic stock returns. J Mark 71(3):75\u201388","journal-title":"J Mark"},{"key":"4937_CR36","doi-asserted-by":"publisher","first-page":"36","DOI":"10.2307\/2325486","volume":"25","author":"EE Fama","year":"1970","unstructured":"Fama EE (1970) Efficient capital markets: a review of theory and empirical work. J Finance 25:36","journal-title":"J Finance"},{"key":"4937_CR37","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1109\/TKDE.2017.2763144","volume":"30","author":"Q Li","year":"2018","unstructured":"Li Q, Chen Y, Wang J et al (2018) Web media and stock markets : a survey and future directions from a big data perspective. IEEE Trans Knowl Data Eng 30:381\u2013399. https:\/\/doi.org\/10.1109\/TKDE.2017.2763144","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"3","key":"4937_CR38","doi-asserted-by":"publisher","first-page":"1139","DOI":"10.1111\/j.1540-6261.2007.01232.x","volume":"62","author":"PC Tetlock","year":"2007","unstructured":"Tetlock PC (2007) Giving content to investor sentiment: the role of media in the stock market. J Finance 62(3):1139\u20131168","journal-title":"J Finance"},{"key":"4937_CR39","doi-asserted-by":"publisher","first-page":"826","DOI":"10.1016\/j.ins.2014.03.096","volume":"278","author":"Q Li","year":"2014","unstructured":"Li Q, Wang T, Li P et al (2014) The effect of news and public mood on stock movements. Inf Sci 278:826\u2013840. https:\/\/doi.org\/10.1016\/j.ins.2014.03.096","journal-title":"Inf Sci"},{"key":"4937_CR40","doi-asserted-by":"publisher","first-page":"9603","DOI":"10.1016\/j.eswa.2015.07.052","volume":"42","author":"TH Nguyen","year":"2015","unstructured":"Nguyen TH, Shirai K, Velcin J (2015) Sentiment analysis on social media for stock movement prediction. Expert Syst Appl 42:9603\u20139611. https:\/\/doi.org\/10.1016\/j.eswa.2015.07.052","journal-title":"Expert Syst Appl"},{"key":"4937_CR41","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.dss.2014.01.013","volume":"61","author":"Q Li","year":"2014","unstructured":"Li Q, Wang T, Gong Q et al (2014) Media-aware quantitative trading based on public Web information. Decis Support Syst 61:93\u2013105. https:\/\/doi.org\/10.1016\/j.dss.2014.01.013","journal-title":"Decis Support Syst"},{"key":"4937_CR42","doi-asserted-by":"crossref","unstructured":"Si J, Mukherjee A, Liu B et al (2014) Exploiting social relations and sentiment for stock prediction. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP). Association for Computational Linguistics, Doha, Qatar, pp 1139\u20131145","DOI":"10.3115\/v1\/D14-1120"},{"key":"4937_CR43","doi-asserted-by":"crossref","unstructured":"Cheng J, Zhao S, Zhang J et al (2017) Aspect-level sentiment classification with HEAT (HiErarchical ATtention) network. In: Proceedings of the 2017 ACM on conference on information and knowledge management\u2014CIKM\u201917. ACM Press, Singapore, pp 97\u2013106","DOI":"10.1145\/3132847.3133037"},{"key":"4937_CR44","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1145\/2602574","volume":"57","author":"W Fan","year":"2014","unstructured":"Fan W, Gordon MD (2014) The power of social media analytics. Commun ACM 57:74\u201381. https:\/\/doi.org\/10.1145\/2602574","journal-title":"Commun ACM"},{"key":"4937_CR45","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1007\/s10462-017-9588-9","volume":"50","author":"FZ Xing","year":"2018","unstructured":"Xing FZ, Cambria E, Welsch RE (2018) Natural language based financial forecasting: a survey. Artif Intell Rev 50:49\u201373. https:\/\/doi.org\/10.1007\/s10462-017-9588-9","journal-title":"Artif Intell Rev"},{"key":"4937_CR46","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1016\/j.ijforecast.2014.05.006","volume":"31","author":"T Kim","year":"2015","unstructured":"Kim T, Hong J, Kang P (2015) Box office forecasting using machine learning algorithms based on SNS data. Int J Forecast 31:364\u2013390. https:\/\/doi.org\/10.1016\/j.ijforecast.2014.05.006","journal-title":"Int J Forecast"},{"key":"4937_CR47","doi-asserted-by":"publisher","first-page":"1680","DOI":"10.1016\/j.eswa.2013.08.065","volume":"41","author":"J Du","year":"2014","unstructured":"Du J, Xu H, Huang X (2014) Box office prediction based on microblog. Expert Syst Appl 41:1680\u20131689. https:\/\/doi.org\/10.1016\/j.eswa.2013.08.065","journal-title":"Expert Syst Appl"},{"key":"4937_CR48","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.eswa.2019.01.012","volume":"124","author":"BM Henrique","year":"2019","unstructured":"Henrique BM, Sobreiro VA, Kimura H (2019) Literature review: machine learning techniques applied to financial market prediction. Expert Syst Appl 124:226\u2013251. https:\/\/doi.org\/10.1016\/j.eswa.2019.01.012","journal-title":"Expert Syst Appl"},{"key":"4937_CR49","unstructured":"Ding X, Zhang Y, Liu T, Duan J (2015) Deep learning for event-driven stock prediction. In: Twenty-fourth international joint conference on artificial intelligence"},{"key":"4937_CR50","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.dss.2017.10.001","volume":"104","author":"M Kraus","year":"2017","unstructured":"Kraus M, Feuerriegel S (2017) Decision support from financial disclosures with deep neural networks and transfer learning. Decis Support Syst 104:38\u201348. https:\/\/doi.org\/10.1016\/j.dss.2017.10.001","journal-title":"Decis Support Syst"},{"key":"4937_CR51","doi-asserted-by":"crossref","unstructured":"He R, Lee WS, Ng HT, Dahlmeier D (2018) Exploiting document knowledge for aspect-level sentiment classification. arXiv:180604346[cs]","DOI":"10.18653\/v1\/P18-2092"},{"key":"4937_CR52","first-page":"572","volume-title":"Attention modeling for targeted sentiment","author":"J Liu","year":"2017","unstructured":"Liu J, Zhang Y (2017) Attention modeling for targeted sentiment. Association for Computational Linguistics, Valencia, pp 572\u2013577"},{"key":"4937_CR53","first-page":"261","volume-title":"Listening to chaotic whispers: a deep learning framework for news-oriented stock trend prediction","author":"Z Hu","year":"2018","unstructured":"Hu Z, Liu W, Bian J et al (2018) Listening to chaotic whispers: a deep learning framework for news-oriented stock trend prediction. ACM Press, New york, pp 261\u2013269"},{"key":"4937_CR54","first-page":"1603","volume-title":"Hierarchical complementary attention network for predicting stock price movements with news","author":"Q Liu","year":"2018","unstructured":"Liu Q, Cheng X, Su S, Zhu S (2018) Hierarchical complementary attention network for predicting stock price movements with news. ACM Press, Torino, pp 1603\u20131606"},{"key":"4937_CR55","unstructured":"Ling W, Trancoso I, Dyer C, Black AW (2015) Character-based neural machine translation. arXiv:151104586[cs]"},{"key":"4937_CR56","unstructured":"Golub D, He X (2016) Character-level question answering with attention. arXiv:160400727[cs]"},{"key":"4937_CR57","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.dss.2016.11.002","volume":"94","author":"C Ding","year":"2017","unstructured":"Ding C, Cheng HK, Duan Y, Jin Y (2017) The power of the \u201clike\u201d button: the impact of social media on box office. Decis Support Syst 94:77\u201384. https:\/\/doi.org\/10.1016\/j.dss.2016.11.002","journal-title":"Decis Support Syst"},{"key":"4937_CR58","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/S0306-4573(02)00021-3","volume":"39","author":"A Aizawa","year":"2003","unstructured":"Aizawa A (2003) An information-theoretic perspective of tf\u2013idf measures. Inf Process Manag 39:45\u201365","journal-title":"Inf Process Manag"},{"key":"4937_CR59","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1016\/j.dss.2018.09.002","volume":"115","author":"B Kratzwald","year":"2018","unstructured":"Kratzwald B, Ili\u0107 S, Kraus M et al (2018) Deep learning for affective computing: text-based emotion recognition in decision support. Decis Support Syst 115:24\u201335. https:\/\/doi.org\/10.1016\/j.dss.2018.09.002","journal-title":"Decis Support Syst"},{"key":"4937_CR60","doi-asserted-by":"crossref","unstructured":"Cho K, van Merrienboer B, Gulcehre C et al (2014) Learning phrase representations using RNN encoder\u2013decoder for statistical machine translation. arXiv:14061078[cs,stat]","DOI":"10.3115\/v1\/D14-1179"},{"key":"4937_CR61","unstructured":"Vaswani A, Shazeer N, Parmar N et al (2017) Attention is all you need. arXiv:170603762[cs]"},{"key":"4937_CR62","unstructured":"Mnih V, Heess N, Graves A, Kavukcuoglu K (2014) Recurrent models of visual attention. arXiv:14066247[cs,stat]"},{"key":"4937_CR63","unstructured":"Mikolov T, Chen K, Corrado G, Dean J (2013) Efficient estimation of word representations in vector space. arXiv:13013781[cs]"},{"key":"4937_CR64","first-page":"1532","volume-title":"Glove: global vectors for word representation","author":"J Pennington","year":"2014","unstructured":"Pennington J, Socher R, Manning C (2014) Glove: global vectors for word representation. Association for Computational Linguistics, Doha, pp 1532\u20131543"},{"key":"4937_CR65","doi-asserted-by":"crossref","unstructured":"Kim Y (2014) Convolutional neural networks for sentence classification. arXiv:14085882[cs]","DOI":"10.3115\/v1\/D14-1181"},{"key":"4937_CR66","doi-asserted-by":"publisher","first-page":"982","DOI":"10.1016\/j.jclinepi.2005.02.022","volume":"58","author":"JB Reitsma","year":"2005","unstructured":"Reitsma JB, Glas AS, Rutjes AWS et al (2005) Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 58:982\u2013990. https:\/\/doi.org\/10.1016\/j.jclinepi.2005.02.022","journal-title":"J Clin Epidemiol"},{"key":"4937_CR67","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1109\/MIS.2013.1","volume":"28","author":"C Hung","year":"2013","unstructured":"Hung C, Lin H-K (2013) Using objective words in SentiWordNet to improve word-of-mouth sentiment classification. IEEE Intell Syst 28:47\u201354. https:\/\/doi.org\/10.1109\/MIS.2013.1","journal-title":"IEEE Intell Syst"},{"key":"4937_CR68","doi-asserted-by":"crossref","unstructured":"Li J, Chen X, Hovy E, Jurafsky D (2015) Visualizing and understanding neural models in NLP. arXiv:150601066[cs]","DOI":"10.18653\/v1\/N16-1082"},{"key":"4937_CR69","doi-asserted-by":"publisher","first-page":"e111988","DOI":"10.1371\/journal.pone.0111988","volume":"9","author":"W Deng","year":"2014","unstructured":"Deng W, Wang Y, Liu Z et al (2014) HemI: a toolkit for illustrating heatmaps. PLoS ONE 9:e111988. https:\/\/doi.org\/10.1371\/journal.pone.0111988","journal-title":"PLoS ONE"},{"key":"4937_CR70","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1016\/j.neucom.2018.07.029","volume":"315","author":"C Wu","year":"2018","unstructured":"Wu C, Wei Y, Chu X et al (2018) Hierarchical attention-based multimodal fusion for video captioning. Neurocomputing 315:362\u2013370. https:\/\/doi.org\/10.1016\/j.neucom.2018.07.029","journal-title":"Neurocomputing"},{"key":"4937_CR71","unstructured":"Devlin J, Chang M-W, Lee K, Toutanova K (2018) BERT: pre-training of deep bidirectional transformers for language understanding. arXiv:181004805[cs]"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-04937-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-020-04937-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-020-04937-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,22]],"date-time":"2022-10-22T02:50:30Z","timestamp":1666407030000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-020-04937-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,23]]},"references-count":71,"journal-issue":{"issue":"23","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["4937"],"URL":"https:\/\/doi.org\/10.1007\/s00521-020-04937-0","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,23]]},"assertion":[{"value":"10 September 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 April 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 April 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}