{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:14:32Z","timestamp":1761808472689,"version":"3.41.2"},"reference-count":77,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2021,10,7]],"date-time":"2021-10-07T00:00:00Z","timestamp":1633564800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["DTA"],"published-print":{"date-parts":[[2022,3,15]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>Critical thinking is considered important in psychological science because it enables students to make effective decisions and optimizes their performance. Aiming at the challenges and issues of understanding the student's critical thinking, the objective of this study is to analyze online discussion data through an advanced multi-feature fusion modeling (MFFM) approach for automatically and accurately understanding the student's critical thinking levels.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>An advanced MFFM approach is proposed in this study. Specifically, with considering the time-series characteristic and the high correlations between adjacent words in discussion contents, the long short-term memory\u2013convolutional neural network (LSTM-CNN) architecture is proposed to extract deep semantic features, and then these semantic features are combined with linguistic and psychological knowledge generated by the LIWC2015 tool as the inputs of full-connected layers to automatically and accurately predict students' critical thinking levels that are hidden in online discussion data.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>A series of experiments with 94 students' 7,691 posts were conducted to verify the effectiveness of the proposed approach. The experimental results show that the proposed MFFM approach that combines two types of textual features outperforms baseline methods, and the semantic-based padding can further improve the prediction performance of MFFM. It can achieve 0.8205 overall accuracy and 0.6172 F1 score for the \u201chigh\u201d category on the validation dataset. Furthermore, it is found that the semantic features extracted by LSTM-CNN are more powerful for identifying self-introduction or off-topic discussions, while the linguistic, as well as psychological features, can better distinguish the discussion posts with the highest critical thinking level.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>With the support of the proposed MFFM approach, online teachers can conveniently and effectively understand the interaction quality of online discussions, which can support instructional decision-making to better promote the student's knowledge construction process and improve learning performance.<\/jats:p><\/jats:sec>","DOI":"10.1108\/dta-04-2021-0088","type":"journal-article","created":{"date-parts":[[2021,10,10]],"date-time":"2021-10-10T17:24:14Z","timestamp":1633886654000},"page":"303-326","source":"Crossref","is-referenced-by-count":13,"title":["Analyzing online discussion data for understanding the student's critical thinking"],"prefix":"10.1108","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2004-8613","authenticated-orcid":false,"given":"Juan","family":"Yang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9069-6109","authenticated-orcid":false,"given":"Xu","family":"Du","sequence":"additional","affiliation":[]},{"given":"Jui-Long","family":"Hung","sequence":"additional","affiliation":[]},{"given":"Chih-hsiung","family":"Tu","sequence":"additional","affiliation":[]}],"member":"140","published-online":{"date-parts":[[2021,10,7]]},"reference":[{"key":"key2022031408460275900_ref001","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1016\/j.ipm.2019.02.018","article-title":"Deep-learning based sentiment classification of evaluative text based on multi-feature fusion","volume":"56","year":"2019","journal-title":"Information Processing and Management"},{"key":"key2022031408460275900_ref002","doi-asserted-by":"crossref","unstructured":"Aggarwal, C.C. and Zhai, C.X. (Eds) (2012), Mining Text Data, Springer, New York, NY.","DOI":"10.1007\/978-1-4614-3223-4"},{"volume-title":"AMA 2012 Critical Skills Survey","year":"2012","author":"American Management Association","key":"key2022031408460275900_ref003"},{"volume-title":"The LEAP Vision for Learning: Outcomes, Practices, Impact, and Employers' View","year":"2011","author":"Association of American Colleges and Universities","key":"key2022031408460275900_ref004"},{"first-page":"615","article-title":"Question answering with subgraph embeddings","year":"2014","key":"key2022031408460275900_ref005"},{"issue":"1","key":"key2022031408460275900_ref006","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","year":"2001","journal-title":"Machine Learning"},{"issue":"2","key":"key2022031408460275900_ref007","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1007\/s10278-017-0027-x","article-title":"Integrating natural language processing and machine learning algorithms to categorize oncologic response in radiology reports","volume":"31","year":"2018","journal-title":"Journal of Digital Imaging"},{"issue":"4","key":"key2022031408460275900_ref008","doi-asserted-by":"crossref","first-page":"787","DOI":"10.2478\/amcs-2018-0060","article-title":"A case study in text mining of discussion forum posts: classification with bag of words and global vectors","volume":"28","year":"2018","journal-title":"International Journal of Applied Mathematics and Computer Science"},{"key":"key2022031408460275900_ref009","doi-asserted-by":"crossref","first-page":"168865","DOI":"10.1109\/ACCESS.2020.3023871","article-title":"Cross-subject multimodal emotion recognition based on hybrid fusion","volume":"8","year":"2020","journal-title":"IEEE ACCESS"},{"issue":"1","key":"key2022031408460275900_ref010","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1097\/00002800-198800210-00025","article-title":"Content analysis: process and application","volume":"2","year":"1988","journal-title":"Clinical Nurse Specialist"},{"issue":"3","key":"key2022031408460275900_ref011","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","year":"1995","journal-title":"Machine Learning"},{"issue":"3","key":"key2022031408460275900_ref012","article-title":"Detecting emotional contagion in massive social networks","volume":"9","year":"2014","journal-title":"PloS One"},{"first-page":"388","article-title":"Language to completion: success in an educational data mining massive open online class","year":"2015","key":"key2022031408460275900_ref013"},{"issue":"2","key":"key2022031408460275900_ref014","first-page":"114","article-title":"The nature of critical thinking","volume":"19","year":"1989","journal-title":"Journal of College Science Teaching"},{"key":"key2022031408460275900_ref015","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.compedu.2018.02.007","article-title":"An exploratory study of student engagement in gamified online discussions","volume":"120","year":"2018","journal-title":"Computers and Education"},{"issue":"1","key":"key2022031408460275900_ref016","first-page":"10110","article-title":"An integrated framework based on latent variational autoencoder for providing early warning of at-risk students","volume":"8","year":"2020","journal-title":"IEEE ACCESS"},{"issue":"2","key":"key2022031408460275900_ref017","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1177\/0956797614557867","article-title":"Psychological language on Twitter predicts county-level heart disease mortality","volume":"26","year":"2015","journal-title":"Psychological Science"},{"issue":"1","key":"key2022031408460275900_ref018","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1111\/j.1365-2648.2007.04569.x","article-title":"The qualitative content analysis process","volume":"62","year":"2008","journal-title":"Journal of Advanced Nursing"},{"issue":"6","key":"key2022031408460275900_ref019","first-page":"1","article-title":"Text mining in education","volume":"9","year":"2019","journal-title":"Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery"},{"issue":"10","key":"key2022031408460275900_ref020","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1037\/0003-066X.34.10.906","article-title":"Metacognition and cognitive monitoring: a new area of cognitive\u2013developmental inquiry","volume":"34","year":"1979","journal-title":"American Psychologist"},{"issue":"2-3","key":"key2022031408460275900_ref021","first-page":"131","article-title":"Bayesian network classifiers","volume":"29","year":"1997","journal-title":"Machine Learning"},{"issue":"3","key":"key2022031408460275900_ref022","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1207\/s15389286ajde1903_2","article-title":"Facilitating cognitive presence in online learning: interaction is not enough","volume":"19","year":"2005","journal-title":"The American Journal of Distance Education"},{"issue":"1","key":"key2022031408460275900_ref023","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1080\/08923640109527071","article-title":"Critical thinking, cognitive presence, and computer conferencing in distance education","volume":"15","year":"2001","journal-title":"American Journal of Distance Education"},{"key":"key2022031408460275900_ref024","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.neucom.2019.08.096","article-title":"Semantic-based padding in convolutional neural networks for improving the performance in natural language processing. A case of study in sentiment analysis","volume":"378","year":"2020","journal-title":"Neurocomputing"},{"key":"key2022031408460275900_ref025","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.eswa.2019.03.036","article-title":"Behind the cues: a benchmarking study for fake news detection","volume":"128","year":"2019","journal-title":"Expert Systems with Applications"},{"issue":"4","key":"key2022031408460275900_ref026","doi-asserted-by":"crossref","first-page":"397","DOI":"10.2190\/7MQV-X9UJ-C7Q3-NRAG","article-title":"Analysis of a global online debate and the development of an interaction analysis model for examining social construction of knowledge in computer conferencing","volume":"17","year":"1997","journal-title":"Journal of Educational Computing Research"},{"issue":"4","key":"key2022031408460275900_ref027","doi-asserted-by":"crossref","first-page":"237","DOI":"10.3109\/11038128.2015.1004103","article-title":"Client-centred occupational therapy: the importance of critical perspectives","volume":"22","year":"2015","journal-title":"Scandinavian Journal of Occupational Therapy"},{"key":"key2022031408460275900_ref028","first-page":"102","article-title":"Towards a real-time processing framework based on improved distributed recurrent neural network variants with fastText for social big data analytics","volume":"57","year":"2020","journal-title":"Information Processing and Management"},{"key":"key2022031408460275900_ref029","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1362\/146934703771910080","article-title":"An overview of content analysis","volume":"3","year":"2003","journal-title":"The Marketing Review"},{"issue":"2","key":"key2022031408460275900_ref030","article-title":"A content analytic comparison of learning processes in online and face-to-face case study discussions","volume":"10","year":"2005","journal-title":"Journal of Computer-Mediated Communication"},{"key":"key2022031408460275900_ref031","doi-asserted-by":"crossref","unstructured":"Henri, F. (1992), \u201cComputer conferencing and content analysis\u201d, in Kaye, A. (Ed.), Collaborative Learning through Computer Conferencing: the Najaden Papers, Springer-Verlag, Berlin, pp. 117-136.","DOI":"10.1007\/978-3-642-77684-7_8"},{"key":"key2022031408460275900_ref032","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.knosys.2019.01.019","article-title":"Image-text sentiment analysis via deep multimodal attentive fusion","volume":"167","year":"2019","journal-title":"Knowledge-Based Systems"},{"key":"key2022031408460275900_ref033","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1111\/jcal.12168","article-title":"Three interaction patterns on asynchronous online discussion behaviours: a methodological comparison","volume":"33","year":"2017","journal-title":"Journal of Computer Assisted Learning"},{"key":"key2022031408460275900_ref034","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.iheduc.2014.03.001","article-title":"Psychological characteristics in cognitive presence of communities of inquiry: a linguistic analysis of online discussions","volume":"22","year":"2014","journal-title":"Internet and Higher Education"},{"issue":"4","key":"key2022031408460275900_ref035","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1007\/s10639-014-9353-5","article-title":"Beyond traditional literacy: learning and transformative practices using ICT","volume":"21","year":"2016","journal-title":"Education and Information Technologies"},{"key":"key2022031408460275900_ref036","unstructured":"Kim, Y. (2014), \u201cConvolutional neural networks for sentence classification\u201d, arXiv Preprint, arXiv:1408.5882, available at: http:\/\/de.arxiv.org\/pdf\/1408.5882."},{"issue":"3","key":"key2022031408460275900_ref037","first-page":"89","article-title":"A multidimensional analysis tool for visualizing online interactions","volume":"15","year":"2012","journal-title":"Journal of Educational Technology and Society"},{"issue":"2","key":"key2022031408460275900_ref038","first-page":"155","article-title":"Leveraging ideas from user innovation communities: using text-mining and case-based reasoning","volume":"49","year":"2017","journal-title":"R&D Management"},{"key":"key2022031408460275900_ref039","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1016\/j.cogsys.2019.09.003","article-title":"Intelligent technologies to optimize performance: augmenting cognitive capacity and supporting self-regulation of critical thinking skills in decision-making","volume":"58","year":"2019","journal-title":"Cognitive Systems Research"},{"issue":"4","key":"key2022031408460275900_ref040","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1007\/s11251-017-9412-6","article-title":"Effects of discussion representation: comparisons between social and cognitive diagrams","volume":"45","year":"2017","journal-title":"Instructional Science"},{"key":"key2022031408460275900_ref041","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.jslw.2016.10.003","article-title":"The relationship between lexical sophistication and independent and source-based writing","volume":"34","year":"2016","journal-title":"Journal of Second Language Writing"},{"key":"key2022031408460275900_ref042","first-page":"1030","article-title":"The tool for the automatic analysis of lexical sophistication (TAALES): version 2.0","volume":"50","year":"2017","journal-title":"Behavior Research Methods"},{"key":"key2022031408460275900_ref043","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","year":"2015","journal-title":"Nature"},{"issue":"2","key":"key2022031408460275900_ref044","first-page":"243","article-title":"Mining online discussion data for understanding teachers' reflective thinking","volume":"11","year":"2017","journal-title":"IEEE Transactions on Learning Technologies"},{"key":"key2022031408460275900_ref045","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.tourman.2017.11.005","article-title":"Utilitarianism and knowledge growth during status seeking: evidence from text mining of online reviews","volume":"66","year":"2018","journal-title":"Tourism Management"},{"key":"key2022031408460275900_ref046","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1016\/j.chb.2013.07.050","article-title":"Assessing social construction of knowledge online: a critique of the interaction analysis model","volume":"30","year":"2014","journal-title":"Computers in Human Behavior"},{"issue":"12","key":"key2022031408460275900_ref047","doi-asserted-by":"crossref","first-page":"2127","DOI":"10.1109\/TASLP.2019.2942160","article-title":"Global-local mutual attention model for text classification","volume":"27","year":"2019","journal-title":"IEEE-ACM Transactions on Audio Speech and Language Processing"},{"key":"key2022031408460275900_ref048","unstructured":"Mikolov, T., Chen, K., Corrado, G.S. and Dean, J. (2013), \u201cEfficient estimation of word representations in vector space\u201d, arXiv:1301.3781, available at: https:\/\/arxiv.org\/abs\/1301.3781."},{"year":"2018","key":"key2022031408460275900_ref049","article-title":"Advances in pre-training distributed word representations"},{"issue":"2","key":"key2022031408460275900_ref050","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/08923648909526659","article-title":"Three types of interaction","volume":"3","year":"1989","journal-title":"American Journal of Distance Education"},{"key":"key2022031408460275900_ref051","first-page":"1021","article-title":"Opinion spam detection: using multi-iterative graph-based model","volume":"57","year":"2020","journal-title":"Information Processing and Management"},{"key":"key2022031408460275900_ref052","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1007\/s12528-018-9180-6","article-title":"Facilitating critical thinking in asynchronous online discussion: comparison between peer- and instructor-redirection","volume":"30","year":"2018","journal-title":"Journal of Computing in Higher Education"},{"issue":"12","key":"key2022031408460275900_ref053","article-title":"When small words foretell academic success: the case of college admissions essays","volume":"9","year":"2014","journal-title":"PLoS ONE"},{"volume-title":"The Development and Psychometric Properties of LIWC2015","year":"2015","key":"key2022031408460275900_ref054"},{"issue":"4","key":"key2022031408460275900_ref055","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1177\/0261927X13476869","article-title":"Predicting final course performance from students' written self-introductions: a LIWC analysis","volume":"32","year":"2013","journal-title":"Journal of Language and Social Psychology"},{"issue":"6","key":"key2022031408460275900_ref056","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1080\/02602938.2018.1556776","article-title":"A multi-level modeling approach to investigating students' critical thinking at higher education institutions","volume":"44","year":"2019","journal-title":"Assessment and Evaluation in Higher Education"},{"issue":"1","key":"key2022031408460275900_ref057","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/505282.505283","article-title":"Machine learning in automated text categorization","volume":"34","year":"2002","journal-title":"ACM Computing Surveys"},{"first-page":"137","article-title":"Spam detection in social media employing machine learning tool for text mining","year":"2017","key":"key2022031408460275900_ref058"},{"first-page":"3056","article-title":"Tracking-by-segmentation with online gradient boosting decision tree","year":"2015","key":"key2022031408460275900_ref059"},{"issue":"1","key":"key2022031408460275900_ref060","article-title":"A multimodal fake news detection model based on crossmodal attention residual and multichannel convolutional neural networks","volume":"58","year":"2021","journal-title":"Information Processing and Management"},{"issue":"3","key":"key2022031408460275900_ref061","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1504\/IJLT.2014.065749","article-title":"The relationship between cognitive disequilibrium, emotions, and individual differences on student question generation","volume":"9","year":"2014","journal-title":"International Journal of Learning Technology"},{"issue":"3","key":"key2022031408460275900_ref062","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1109\/TASLP.2015.2400218","article-title":"From feedforward to recurrent LSTM neural networks for language modeling","volume":"23","year":"2015","journal-title":"IEEE\/ACM Transactions on Audio, Speech, and Language Processing"},{"key":"key2022031408460275900_ref063","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1007\/s12528-017-9135-3","article-title":"The nature and level of learner\u2013learner interaction in a chemistry massive open online course (MOOC)","volume":"29","year":"2017","journal-title":"Journal of Computing in Higher Education"},{"key":"key2022031408460275900_ref064","doi-asserted-by":"crossref","unstructured":"Ting, K.M. (2017), \u201cConfusion matrix\u201d, in Sammut, C. and Webb, G.I. (Eds), Encyclopedia of Machine Learning and Data Mining, Springer, Boston, MA, p. 9, doi: 10.1007\/978-1-4899-7687-1_50.","DOI":"10.1007\/978-1-4899-7687-1_50"},{"first-page":"178","article-title":"Predicting elections with Twitter: what 140 characters reveal about political sentiment","year":"2010","key":"key2022031408460275900_ref065"},{"issue":"2","key":"key2022031408460275900_ref066","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1080\/09720502.2017.1420567","article-title":"Effects of online learning communities on college students' knowledge learning and construction","volume":"21","year":"2018","journal-title":"Journal of Interdisciplinary Mathematics"},{"key":"key2022031408460275900_ref067","first-page":"25","article-title":"Theory framework building of instructional interaction in connectivist learning context","volume":"5","year":"2015","journal-title":"The Journal of Open Educational Research"},{"issue":"2","key":"key2022031408460275900_ref068","first-page":"121","article-title":"A framework for interaction and cognitive engagement in connectivist learning contexts","volume":"15","year":"2014","journal-title":"The International Review of Research in Open and Distributed Learning"},{"issue":"2","key":"key2022031408460275900_ref069","first-page":"683","article-title":"Interaction pattern analysis in cMOOCs based on the connectivist interaction and engagement framework","volume":"48","year":"2016","journal-title":"British Journal of Educational Technology"},{"key":"key2022031408460275900_ref070","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/j.jbi.2016.08.026","article-title":"A part-of-speech term weighting scheme for biomedical information retrieval","volume":"63","year":"2016","journal-title":"Journal of Biomedical Informatics"},{"volume-title":"Data Mining: Theory, Methodology, Techniques, and Application","year":"2006","key":"key2022031408460275900_ref071"},{"key":"key2022031408460275900_ref072","doi-asserted-by":"crossref","first-page":"59844","DOI":"10.1109\/ACCESS.2019.2914872","article-title":"Exploiting EEG signals and audiovisual feature fusion for video emotion recognition","volume":"7","year":"2019","journal-title":"IEEE Access"},{"issue":"3","key":"key2022031408460275900_ref073","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1109\/MCI.2018.2840738","article-title":"Recent trends in deep learning based natural language processing","volume":"13","year":"2018","journal-title":"IEEE Computational Intelligence Magazine"},{"key":"key2022031408460275900_ref074","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.future.2021.03.024","article-title":"Multi-dimensional feature fusion and stacking ensemble mechanism for network intrusion detection","volume":"122","year":"2021","journal-title":"Future Generation Computer Systems"},{"issue":"2","key":"key2022031408460275900_ref075","doi-asserted-by":"crossref","first-page":"794","DOI":"10.1109\/TFUZZ.2017.2690222","article-title":"Fuzzy bag-of-words model for document representation","volume":"26","year":"2018","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"key2022031408460275900_ref076","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1080\/01587919.2019.1600365","article-title":"Exploring presence in online learning through three forms of computer-mediated discourse analysis","volume":"40","year":"2019","journal-title":"Distance Education"},{"volume-title":"The Secret Life of Pronouns","year":"2011","key":"key2022031408460275900_fur1"}],"container-title":["Data Technologies and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/DTA-04-2021-0088\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/DTA-04-2021-0088\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T23:15:05Z","timestamp":1753398905000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/dta\/article\/56\/2\/303-326\/101756"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,7]]},"references-count":77,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,10,7]]},"published-print":{"date-parts":[[2022,3,15]]}},"alternative-id":["10.1108\/DTA-04-2021-0088"],"URL":"https:\/\/doi.org\/10.1108\/dta-04-2021-0088","relation":{},"ISSN":["2514-9288"],"issn-type":[{"type":"print","value":"2514-9288"}],"subject":[],"published":{"date-parts":[[2021,10,7]]}}}