{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T01:36:17Z","timestamp":1777599377502,"version":"3.51.4"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2020,5,22]],"date-time":"2020-05-22T00:00:00Z","timestamp":1590105600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,5,22]],"date-time":"2020-05-22T00:00:00Z","timestamp":1590105600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Spanish MINECO and FEDER Project","award":["TIN2017-85854-C4-2-R"],"award-info":[{"award-number":["TIN2017-85854-C4-2-R"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1007\/s11063-020-10260-5","type":"journal-article","created":{"date-parts":[[2020,5,22]],"date-time":"2020-05-22T09:03:21Z","timestamp":1590138201000},"page":"3199-3215","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Cross-Domain Polarity Models to Evaluate User eXperience in E-learning"],"prefix":"10.1007","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5660-8937","authenticated-orcid":false,"given":"Rosario","family":"Sanchis-Font","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1001-8258","authenticated-orcid":false,"given":"Maria Jose","family":"Castro-Bleda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3812-5792","authenticated-orcid":false,"given":"Jos\u00e9-\u00c1ngel","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4822-8808","authenticated-orcid":false,"given":"Ferran","family":"Pla","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1877-0455","authenticated-orcid":false,"given":"Llu\u00eds-F.","family":"Hurtado","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,5,22]]},"reference":[{"key":"10260_CR1","unstructured":"Ba J, Kiros JR, Hinton GE (2016) Layer normalization. arxiv:1607.06450"},{"key":"10260_CR2","unstructured":"Bahdanau D, Cho K, Bengio Y (2015) Neural machine translation by jointly learning to align and translate. In: 3rd international conference on learning representations, ICLR 2015, San Diego, CA, USA, May 7\u20139, 2015, conference track proceedings. arxiv:1409.0473"},{"key":"10260_CR3","doi-asserted-by":"crossref","unstructured":"Baziotis C, Pelekis N, Doulkeridis C (2017) Datastories at SemEval-2017 task 4: deep LSTM with attention for message-level and topic-based sentiment analysis. In: Proceedings of the 11th international workshop on semantic evaluation (SemEval-2017). Association for Computational Linguistics, Vancouver, Canada, pp 747\u2013754","DOI":"10.18653\/v1\/S17-2126"},{"key":"10260_CR4","doi-asserted-by":"publisher","unstructured":"Cliche M (2017) BB\\_twtr at SemEval-2017 task 4: Twitter sentiment analysis with CNNs and LSTMs. In: Proceedings of the 11th international workshop on semantic evaluation (SemEval-2017). Association for Computational Linguistics, Vancouver, Canada, pp 573\u2013580. https:\/\/doi.org\/10.18653\/v1\/S17-2094. https:\/\/www.aclweb.org\/anthology\/S17-2094","DOI":"10.18653\/v1\/S17-2094"},{"issue":"1","key":"10260_CR5","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1177\/001316446002000104","volume":"20","author":"J Cohen","year":"1960","unstructured":"Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20(1):37","journal-title":"Educ Psychol Meas"},{"key":"10260_CR6","doi-asserted-by":"publisher","unstructured":"Devlin J, Chang MW, Lee K, Toutanova K (2019) BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 conference of the North American chapter of the Association for Computational Linguistics: Human Language Technologies, volume 1 (long and short papers). Association for Computational Linguistics, Minneapolis, Minnesota, pp 4171\u20134186. https:\/\/doi.org\/10.18653\/v1\/N19-1423. https:\/\/www.aclweb.org\/anthology\/N19-1423","DOI":"10.18653\/v1\/N19-1423"},{"key":"10260_CR7","unstructured":"Diaz-Galiano MC, et al (2019) Overview of TASS 2019: one more further for the global Spanish sentiment analysis corpus. In: Proceedings of the Iberian languages evaluation forum (IberLEF 2019), CEUR-WS, Bilbao, Spain, CEUR workshop proceedings, pp 550\u2013560"},{"key":"10260_CR8","doi-asserted-by":"publisher","unstructured":"Godin F, Vandersmissen B, De Neve W, Van de Walle R (2015) Multimedia lab @ ACL WNUT NER shared task: named entity recognition for Twitter microposts using distributed word representations. In: Proceedings of the workshop on noisy user-generated text. Association for Computational Linguistics, Beijing, China, pp 146\u2013153. https:\/\/doi.org\/10.18653\/v1\/W15-4322. https:\/\/www.aclweb.org\/anthology\/W15-4322","DOI":"10.18653\/v1\/W15-4322"},{"key":"10260_CR9","unstructured":"Gonz\u00e1lez J, Pla F, Hurtado L (2018) Elirf-upv en TASS 2018: An\u00e1lisis de sentimientos en twitter basado en aprendizaje profundo (elirf-upv at TASS 2018: sentiment analysis in Twitter based on deep learning). In: Proceedings of TASS 2018: workshop on semantic analysis at SEPLN, TASS@SEPLN 2018, co-located with 34nd SEPLN conference (SEPLN 2018), Sevilla, Spain, September 18th, 2018, pp 37\u201344. http:\/\/ceur-ws.org\/Vol-2172\/p2_elirf_tass2018.pdf"},{"key":"10260_CR10","unstructured":"Gonz\u00e1lez J, Hurtado L, Pla F (2019) Elirf-upv at TASS 2019: transformer encoders for Twitter sentiment analysis in Spanish. In: Proceedings of the Iberian languages evaluation forum co-located with 35th conference of the Spanish Society for Natural Language Processing, IberLEF@SEPLN 2019, Bilbao, Spain, September 24th, 2019, pp 571\u2013578. http:\/\/ceur-ws.org\/Vol-2421\/TASS_paper_2.pdf"},{"key":"10260_CR11","doi-asserted-by":"publisher","unstructured":"Gonz\u00e1lez J\u00c1, Pla F, Hurtado LF (2017) ELiRF-UPV at SemEval-2017 task 4: sentiment analysis using deep learning. In: Proceedings of the 11th international workshop on semantic evaluation (SemEval-2017). Association for Computational Linguistics, Vancouver, Canada, pp 723\u2013727. https:\/\/doi.org\/10.18653\/v1\/S17-2121. https:\/\/www.aclweb.org\/anthology\/S17-2121","DOI":"10.18653\/v1\/S17-2121"},{"key":"10260_CR12","unstructured":"Gonz\u00e1lez J\u00c1, Hurtado LF, Pla F (2019) ELiRF-UPV at TASS 2019: transformer encoders for Twitter sentiment analysis in Spanish. In: Proceedings of the Iberian languages evaluation forum (IberLEF 2019), CEUR-WS, Bilbao, Spain, CEUR workshop proceedings"},{"key":"10260_CR13","unstructured":"GoogleCloud (2019) Cloud natural language API. https:\/\/cloud.google.com\/natural-language\/. Accessed 27 Dec 2019"},{"issue":"2","key":"10260_CR14","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1080\/01449290500330331","volume":"25","author":"M Hassenzahl","year":"2006","unstructured":"Hassenzahl M, Tractinsky N (2006) User experience\u2014a research agenda. Behav Inf Technol 25(2):91\u201397. https:\/\/doi.org\/10.1080\/01449290500330331","journal-title":"Behav Inf Technol"},{"issue":"8","key":"10260_CR15","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. https:\/\/doi.org\/10.1162\/neco.1997.9.8.1735","journal-title":"Neural Comput"},{"key":"10260_CR16","unstructured":"Hurtado\u00a0Oliver LF, Pla F, Gonz\u00e1lez\u00a0Barba J (2017) ELiRF-UPV at TASS 2017: sentiment analysis in Twitter based on deep learning. In: TASS 2017: workshop on semantic analysis at SEPLN, pp 29\u201334"},{"key":"10260_CR17","unstructured":"IBM (2019) Natural language understanding. https:\/\/www.ibm.com\/watson\/services\/natural-language-understanding\/. Accessed 27 Dec 2019"},{"key":"10260_CR18","unstructured":"ISO 9241-210:2019 (2019) Ergonomics of human-system interaction\u2014part 210: human-centred design for interactive systems. International Standardization Organization (ISO). https:\/\/www.iso.org\/standard\/77520.html. Accessed 27 Dec 2019"},{"key":"10260_CR19","unstructured":"Kim Y (2014) Convolutional neural networks for sentence classification. In: Proceedings of the 2014 conference on empirical methods in natural language processing, EMNLP 2014, October 25\u201329, 2014, Doha, Qatar, a meeting of SIGDAT, a special interest group of the ACL, pp 1746\u20131751. http:\/\/aclweb.org\/anthology\/D\/D14\/D14-1181.pdf"},{"issue":"3","key":"10260_CR20","first-page":"411","volume":"30","author":"K Krippendorff","year":"2004","unstructured":"Krippendorff K (2004) Reliability in content analysis. Hum Commun Res 30(3):411\u2013433","journal-title":"Hum Commun Res"},{"issue":"5","key":"10260_CR21","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1016\/j.intcom.2011.06.005","volume":"23","author":"S Kujala","year":"2011","unstructured":"Kujala S, Roto V, V\u00e4\u00e4n\u00e4nen-Vainio-Mattila K, Karapanos E, Sinnel\u00e4 A (2011) UX curve: a method for evaluating long-term user experience. Interact Comput 23(5):473\u2013483","journal-title":"Interact Comput"},{"key":"10260_CR22","volume-title":"Sentiment analysis and opinion mining. A comprehensive introduction and survey","author":"B Liu","year":"2012","unstructured":"Liu B (2012) Sentiment analysis and opinion mining. A comprehensive introduction and survey. Morgan & Claypool Publishers, San Rafael"},{"key":"10260_CR23","doi-asserted-by":"publisher","unstructured":"Liu B, Hu M, Cheng J (2005) Opinion observer: analyzing and comparing opinions on the web. In: Proceedings of the 14th international conference on world wide web. ACM, New York, NY, USA, WWW \u201905, pp 342\u2013351. https:\/\/doi.org\/10.1145\/1060745.1060797","DOI":"10.1145\/1060745.1060797"},{"key":"10260_CR24","unstructured":"Luque FM (2019) Atalaya at TASS 2019: data augmentation and robust embeddings for sentiment analysis. In: Proceedings of the Iberian languages evaluation forum (IberLEF 2019), CEUR-WS, Bilbao, Spain, CEUR workshop proceedings"},{"key":"10260_CR25","doi-asserted-by":"crossref","unstructured":"Manning CD, Surdeanu M, Bauer J, Finkel J, Bethard SJ, McClosky D (2014) The Stanford CoreNLP natural language processing toolkit. In: Association for computational linguistics (ACL) system demonstrations, pp 55\u201360. http:\/\/www.aclweb.org\/anthology\/P\/P14\/P14-5010","DOI":"10.3115\/v1\/P14-5010"},{"key":"10260_CR26","unstructured":"Mart\u00ednez-C\u00e1mara E, D\u00edaz-Galiano M, Garc\u00eda-Cumbreras M, Garc\u00eda-Vega M, Villena-Rom\u00e1n J (2017) Overview of TASS 2017. In: Proceedings of TASS 2017: workshop on semantic analysis at SEPLN (TASS 2017), CEUR-WS, Murcia, Spain, CEUR workshop proceedings, vol 1896"},{"key":"10260_CR27","unstructured":"MeaningCloud (2019) Demo de Anal\u00edtica de Textos. https:\/\/www.meaningcloud.com\/es\/demos\/demo-analitica-textos. Accessed 27 Dec 2019"},{"key":"10260_CR28","unstructured":"MeaningCloud (2019) MeaningCloud: Servicios web de anal\u00edtica y miner\u00eda de textos. https:\/\/www.meaningcloud.com\/. Accessed 27 Dec 2019"},{"key":"10260_CR29","unstructured":"MicrosoftAzure (2019) Text analytics API. https:\/\/azure.microsoft.com\/es-es\/services\/cognitive-services\/text-analytics\/. Accessed 27 Dec 2019"},{"key":"10260_CR30","doi-asserted-by":"crossref","unstructured":"Pang B, Lee L, Vaithyanathan S (2002) Thumbs up? sentiment classification using machine learning techniques. In: Proceedings of the ACL-02 conference on empirical methods in natural language processing, vol 10. Association for Computational Linguistics, pp 79\u201386","DOI":"10.3115\/1118693.1118704"},{"issue":"2","key":"10260_CR31","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1007\/s10579-017-9394-7","volume":"52","author":"F Pla","year":"2018","unstructured":"Pla F, Hurtado LF (2018) Spanish sentiment analysis in Twitter at the TASS workshop. Lang Resour Eval 52(2):645\u2013672. https:\/\/doi.org\/10.1007\/s10579-017-9394-7","journal-title":"Lang Resour Eval"},{"issue":"1","key":"10260_CR32","doi-asserted-by":"publisher","first-page":"39","DOI":"10.9781\/ijimai.2013.215","volume":"2","author":"M Rauschenberger","year":"2013","unstructured":"Rauschenberger M, Schrepp M, Cota MP, Olschner S, Thomaschewski J (2013) Efficient measurement of the user experience of interactive products. How to use the user experience questionnaire (UEQ). Example: Spanish language version. Int J Interact Multimed Artif Intell 2(1):39\u201345. https:\/\/doi.org\/10.9781\/ijimai.2013.215","journal-title":"Int J Interact Multimed Artif Intell"},{"key":"10260_CR33","doi-asserted-by":"publisher","unstructured":"Rosenthal S, Farra N, Nakov P (2017) SemEval-2017 task 4: sentiment analysis in Twitter. In: Proceedings of the 11th international workshop on semantic evaluation (SemEval-2017). Association for Computational Linguistics, Vancouver, Canada, pp 502\u2013518. https:\/\/doi.org\/10.18653\/v1\/S17-2088. https:\/\/www.aclweb.org\/anthology\/S17-2088","DOI":"10.18653\/v1\/S17-2088"},{"key":"10260_CR34","doi-asserted-by":"publisher","first-page":"2745","DOI":"10.1007\/s11063-019-10049-1","volume":"50","author":"H Sadr","year":"2019","unstructured":"Sadr H, Pedram MM, Teshnehlab M (2019) A robust sentiment analysis method based on sequential combination of convolutional and recursive neural networks. Neural Process Lett 50:2745\u20132761. https:\/\/doi.org\/10.1007\/s11063-019-10049-1","journal-title":"Neural Process Lett"},{"key":"10260_CR35","first-page":"609","volume-title":"Advances in computational intelligence. IWANN (2019). Lecture notes in computer science","author":"R Sanchis-Font","year":"2019","unstructured":"Sanchis-Font R, Castro-Bleda M, Gonz\u00e1lez J (2019) Applying sentiment analysis with cross-domain models to evaluate user experience in virtual learning environments. In: Rojas I, Joya G, Catala A (eds) Advances in computational intelligence. IWANN (2019). Lecture notes in computer science, vol 11506. Springer, Cham, pp 609\u2013620"},{"issue":"11","key":"10260_CR36","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.1109\/78.650093","volume":"45","author":"M Schuster","year":"1997","unstructured":"Schuster M, Paliwal K (1997) Bidirectional recurrent neural networks. Trans Signal Process 45(11):2673\u20132681. https:\/\/doi.org\/10.1109\/78.650093","journal-title":"Trans Signal Process"},{"issue":"3","key":"10260_CR37","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1086\/266577","volume":"19","author":"WA Scott","year":"1955","unstructured":"Scott WA (1955) Reliability of content analysis: the case of nominal scale coding. Public Opin Q 19(3):321\u2013325. https:\/\/doi.org\/10.1086\/266577","journal-title":"Public Opin Q"},{"key":"10260_CR38","unstructured":"Socher R, Perelygin A, Wu J, Chuang J, Manning CD, Ng A, Potts C (2013) Recursive deep models for semantic compositionality over a sentiment treebank. In: Proceedings of the 2013 conference on empirical methods in natural language processing. Association for Computational Linguistics, Seattle, Washington, USA, pp 1631\u20131642. https:\/\/www.aclweb.org\/anthology\/D13-1170"},{"key":"10260_CR39","doi-asserted-by":"crossref","unstructured":"Turney PD (2002) Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. In: ACL, pp 417\u2013424. http:\/\/www.aclweb.org\/anthology\/P02-1053.pdf","DOI":"10.3115\/1073083.1073153"},{"key":"10260_CR40","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser L, Polosukhin I (2017) Attention is all you need. In: Proceedings of the 31st international conference on neural information processing systems, NIPS\u201917. Curran Associates Inc., USA, pp 6000\u20136010. http:\/\/dl.acm.org\/citation.cfm?id=3295222.3295349"},{"key":"10260_CR41","doi-asserted-by":"crossref","unstructured":"Wilson T, Hoffmann P, Somasundaran S, Kessler J, Wiebe J, Choi Y, Cardie C, Riloff E, Patwardhan S (2005) OpinionFinder: a system for subjectivity analysis. In: Proceedings of HLT\/EMNLP on interactive demonstrations. Association for Computational Linguistics, pp 34\u201335","DOI":"10.3115\/1225733.1225751"},{"issue":"7","key":"10260_CR42","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1016\/j.ijhcs.2012.05.001","volume":"70","author":"P Zaharias","year":"2012","unstructured":"Zaharias P, Mehlenbacher B (2012) Editorial: exploring user experience (UX) in virtual learning environments. Int J Hum Comput Stud 70(7):475\u2013477. https:\/\/doi.org\/10.1016\/j.ijhcs.2012.05.001","journal-title":"Int J Hum Comput Stud"},{"issue":"4","key":"10260_CR43","doi-asserted-by":"publisher","first-page":"e1253","DOI":"10.1002\/widm.1253","volume":"8","author":"L Zhang","year":"2018","unstructured":"Zhang L, Wang S, Liu B (2018) Deep learning for sentiment analysis: a survey. Wiley Interdiscip Rev Data Min Knowl Discov 8(4):e1253","journal-title":"Wiley Interdiscip Rev Data Min Knowl Discov"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-020-10260-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11063-020-10260-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-020-10260-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,15]],"date-time":"2021-10-15T17:50:45Z","timestamp":1634320245000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11063-020-10260-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,22]]},"references-count":43,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2021,10]]}},"alternative-id":["10260"],"URL":"https:\/\/doi.org\/10.1007\/s11063-020-10260-5","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"value":"1370-4621","type":"print"},{"value":"1573-773X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,22]]},"assertion":[{"value":"22 May 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}