{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T01:42:48Z","timestamp":1772502168604,"version":"3.50.1"},"reference-count":58,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T00:00:00Z","timestamp":1746403200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T00:00:00Z","timestamp":1746403200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71672004"],"award-info":[{"award-number":["71672004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimedia Systems"],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s00530-025-01798-2","type":"journal-article","created":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T23:43:01Z","timestamp":1746402181000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Two-stage dynamic topic modeling approach for identifying consumer demands of animated series"],"prefix":"10.1007","volume":"31","author":[{"given":"Duokui","family":"He","sequence":"first","affiliation":[]},{"given":"Zhongjun","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Qianqian","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Yiran","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yingtong","family":"Lu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,5]]},"reference":[{"key":"1798_CR1","unstructured":"Precedence Research: Animation Market. IOP Publishing Web. https:\/\/www.precedenceresearch.com\/animation-marke. Accessed 18 Jan 2024"},{"key":"1798_CR2","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1007\/s00530-024-01401-0","volume":"30","author":"Q Chen","year":"2024","unstructured":"Chen, Q., Tang, Z., He, D., Zhao, D., Wang, J.: A three-stage quality evaluation method for experience products: taking animation as an example. Multimedia Syst. 30, 203 (2024). https:\/\/doi.org\/10.1007\/s00530-024-01401-0","journal-title":"Multimedia Syst."},{"key":"1798_CR3","unstructured":"GuDuo Media.: Guduo Hotness index ranking. IOP Publishing Web.  https:\/\/d.guduodata.com\/ (2023). Accessed 18 Jan 2024"},{"key":"1798_CR4","doi-asserted-by":"publisher","first-page":"6776","DOI":"10.1080\/00207543.2020.1825861","volume":"59","author":"Z Tang","year":"2021","unstructured":"Tang, Z., Dong, S.: A total sales forecasting method for a new short life-cycle product in the pre-market period based on an improved evidence theory: application to the film industry. Int J Prod Res. 59, 6776\u20136790 (2021). https:\/\/doi.org\/10.1080\/00207543.2020.1825861","journal-title":"Int J Prod Res."},{"key":"1798_CR5","doi-asserted-by":"publisher","first-page":"3803","DOI":"10.1287\/mnsc.2020.3667","volume":"67","author":"S Subramanian","year":"2020","unstructured":"Subramanian, S., Harsha, P.: Demand modeling in the presence of unobserved lost sales. Manage. Sci. 67, 3803\u20133833 (2020). https:\/\/doi.org\/10.1287\/mnsc.2020.3667","journal-title":"Manage. Sci."},{"key":"1798_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbusres.2022.113484","volume":"156","author":"S Pal","year":"2023","unstructured":"Pal, S., Biswas, B., Gupta, R., Kumar, A., Gupta, S.: Exploring the factors that affect user experience in mobile-health applications: a text-mining and machine-learning approach. J. Bus. Res. 156, 113484 (2023). https:\/\/doi.org\/10.1016\/j.jbusres.2022.113484","journal-title":"J. Bus. Res."},{"key":"1798_CR7","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.spc.2019.12.003","volume":"21","author":"C Lang","year":"2020","unstructured":"Lang, C., Li, M., Zhao, L.: Understanding consumers\u2019 online fashion renting experiences: a text-mining approach. Sustain Prod Consump. 21, 132\u2013144 (2020). https:\/\/doi.org\/10.1016\/j.spc.2019.12.003","journal-title":"Sustain Prod Consump."},{"key":"1798_CR8","doi-asserted-by":"publisher","first-page":"2051","DOI":"10.1007\/S10796-022-10356-4\/metrics","volume":"25","author":"Q Zeng","year":"2023","unstructured":"Zeng, Q., Guo, Q., Zhuang, W., Zhang, Y., Fan, W.: Do real-time reviews matter? Examining how bullet screen influences consumers\u2019 purchase intention in live streaming commerce. Inform Syst Front. 25, 2051\u20132067 (2023). https:\/\/doi.org\/10.1007\/S10796-022-10356-4\/metrics","journal-title":"Inform Syst Front."},{"key":"1798_CR9","doi-asserted-by":"publisher","first-page":"15169","DOI":"10.1007\/S11042-018-6894-4\/TABLES\/11","volume":"78","author":"H Jelodar","year":"2019","unstructured":"Jelodar, H., Wang, Y., Yuan, C., Feng, X., Jiang, X., Li, Y., Zhao, L.: Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey. Multimed Tools Appl. 78, 15169\u201315211 (2019). https:\/\/doi.org\/10.1007\/S11042-018-6894-4\/TABLES\/11","journal-title":"Multimed Tools Appl."},{"key":"1798_CR10","doi-asserted-by":"publisher","first-page":"1427","DOI":"10.1109\/TKDE.2020.2992485","volume":"34","author":"J Qiang","year":"2022","unstructured":"Qiang, J., Qian, Z., Li, Y., Yuan, Y., Wu, X.: Short text topic modeling techniques, applications, and performance: a survey. IEEE T Knowl Data En. 34, 1427\u20131445 (2022). https:\/\/doi.org\/10.1109\/TKDE.2020.2992485","journal-title":"IEEE T Knowl Data En."},{"key":"1798_CR11","unstructured":"Miao, Y., Yu, L., Blunsom, P.: Neural variational inference for text processing. International conference on machine learning. 48:1727\u20131736.  https:\/\/proceedings.mlr.press\/v48\/miao16.html (2016). Accessed 18 Jan 2024"},{"key":"1798_CR12","doi-asserted-by":"publisher","unstructured":"Srivastava, A., Sutton, C. (2017) Autoencoding variational inference for topic models. 5th International Conference on Learning Representations, ICLR 2017 Conference Track Proceedings. https:\/\/doi.org\/10.48550\/arXiv.1703.01488","DOI":"10.48550\/arXiv.1703.01488"},{"key":"1798_CR13","doi-asserted-by":"publisher","unstructured":"Peng, M., Xie, Q., Zhang, Y., Wang, H., Zhang, X., Huang, J., Tian, G. (2018) Neural Sparse Topical Coding. ACL 2018\u201456th Annual Meeting of the Association for Computational Linguistics. Proceedings of the Conference (Long Papers). 1:2332\u20132340. https:\/\/doi.org\/10.18653\/V1\/P18-1217","DOI":"10.18653\/V1\/P18-1217"},{"key":"1798_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/J.KNOSYS.2024.111650","volume":"293","author":"Z Zhang","year":"2024","unstructured":"Zhang, Z., Li, Z., Zhu, J., Guo, Z., Shi, B., Hu, B.: Enhancing user sequence representation with cross-view collaborative learning for depression detection on Sina Weibo. Knowl.-Based Syst. 293, 111650 (2024). https:\/\/doi.org\/10.1016\/J.KNOSYS.2024.111650","journal-title":"Knowl.-Based Syst."},{"key":"1798_CR15","doi-asserted-by":"publisher","first-page":"205","DOI":"10.21105\/JOSS.00205","volume":"2","author":"L McInnes","year":"2017","unstructured":"McInnes, L., Healy, J., Astels, S.: hdbscan: hierarchical density based clustering. J Open Sourc Softw. 2, 205 (2017). https:\/\/doi.org\/10.21105\/JOSS.00205","journal-title":"J Open Sourc Softw."},{"key":"1798_CR16","doi-asserted-by":"publisher","first-page":"725","DOI":"10.1109\/TNNLS.2019.2909425","volume":"31","author":"X Chen","year":"2020","unstructured":"Chen, X., Chen, R., Wu, Q., Fang, Y., Nie, F., Huang, J.Z.: LABIN: balanced min cut for large-scale data. IEEE T Neur Net Lear. 31, 725\u2013736 (2020). https:\/\/doi.org\/10.1109\/TNNLS.2019.2909425","journal-title":"IEEE T Neur Net Lear."},{"key":"1798_CR17","doi-asserted-by":"publisher","first-page":"101582","DOI":"10.1016\/J.IS.2020.101582","volume":"94","author":"I Vayansky","year":"2020","unstructured":"Vayansky, I., Kumar, S.A.P.: A review of topic modeling methods. Inf Syst. 94, 101582 (2020). https:\/\/doi.org\/10.1016\/J.IS.2020.101582","journal-title":"Inf Syst."},{"key":"1798_CR18","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1109\/TKDE.2020.2982148","volume":"34","author":"S Najafipour","year":"2020","unstructured":"Najafipour, S., Hosseini, S., Hua, W., Kangavari, M.R., Zhou, X.: SoulMate: short-text author linking through Multi-aspect temporal-textual embedding. IEEE T Knowl Data En. 34, 448\u2013461 (2020). https:\/\/doi.org\/10.1109\/TKDE.2020.2982148","journal-title":"IEEE T Knowl Data En."},{"key":"1798_CR19","doi-asserted-by":"publisher","first-page":"103013","DOI":"10.1016\/j.jretconser.2022.103013","volume":"68","author":"Y Xiao","year":"2022","unstructured":"Xiao, Y., Li, C., Th\u00fcrer, M., Liu, Y., Qu, T.: User preference mining based on fine-grained sentiment analysis. J Retail Consum Serv. 68, 103013 (2022). https:\/\/doi.org\/10.1016\/j.jretconser.2022.103013","journal-title":"J Retail Consum Serv."},{"key":"1798_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.jretconser.2023.103598","volume":"76","author":"P Shah","year":"2024","unstructured":"Shah, P., Mehta, N., Shah, S.: Exploring the factors that drive millet consumption: insights from regular and occasional consumers. J. Retail. Consum. Serv. 76, 103598 (2024). https:\/\/doi.org\/10.1016\/j.jretconser.2023.103598","journal-title":"J. Retail. Consum. Serv."},{"key":"1798_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.jretconser.2023.103613","volume":"76","author":"M Hitka","year":"2024","unstructured":"Hitka, M., Miklo\u0161\u00edk, A., Gejdo\u0161, M., \u0160tarcho\u0148, P.: Insights into consumer preferences and purchasing behaviour for wooden bed furniture in Slovakia. J. Retail. Consum. Serv. 76, 103613 (2024). https:\/\/doi.org\/10.1016\/j.jretconser.2023.103613","journal-title":"J. Retail. Consum. Serv."},{"key":"1798_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2023.114088","volume":"177","author":"F Zhou","year":"2024","unstructured":"Zhou, F., Jiang, Y., Qian, Y., Liu, Y., Chai, Y.: Product consumptions meet reviews: Inferring consumer preferences by an explainable machine learning approach. Decis. Support. Syst. 177, 114088 (2024). https:\/\/doi.org\/10.1016\/j.dss.2023.114088","journal-title":"Decis. Support. Syst."},{"key":"1798_CR23","doi-asserted-by":"publisher","first-page":"1800","DOI":"10.1108\/INTR-03-2022-0178","volume":"34","author":"YK Oh","year":"2023","unstructured":"Oh, Y.K., Yi, J., Kim, J.: What enhances or worsens the user-generated metaverse experience? An application of BERTopic to Roblox user eWOM. Internet Res. 34, 1800\u20131817 (2023). https:\/\/doi.org\/10.1108\/INTR-03-2022-0178","journal-title":"Internet Res."},{"key":"1798_CR24","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1108\/JFMM-10-2022-0208","volume":"28","author":"X Pan","year":"2023","unstructured":"Pan, X., Li, J., Luo, J., Zhan, W.: How to discover consumer attention to design topics of fast fashion: a topic modeling approach. J. Fash. Mark. Manag. 28, 273\u2013297 (2023). https:\/\/doi.org\/10.1108\/JFMM-10-2022-0208","journal-title":"J. Fash. Mark. Manag."},{"key":"1798_CR25","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1016\/j.jbusres.2018.08.009","volume":"121","author":"S Moro","year":"2020","unstructured":"Moro, S., Pires, G., Rita, P., Cortez, P.: A cross-cultural case study of consumers\u2019 communications about a new technological product. J. Bus. Res. 121, 438\u2013447 (2020). https:\/\/doi.org\/10.1016\/j.jbusres.2018.08.009","journal-title":"J. Bus. Res."},{"key":"1798_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.jretconser.2023.103588","volume":"76","author":"B Ma","year":"2024","unstructured":"Ma, B., Wong, Y.D., Teo, C.C., Wang, Z.: Enhance understandings of Online Food Delivery\u2019s service quality with online reviews. J. Retail. Consum. Serv. 76, 103588 (2024). https:\/\/doi.org\/10.1016\/j.jretconser.2023.103588","journal-title":"J. Retail. Consum. Serv."},{"key":"1798_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.jretconser.2022.103253","volume":"72","author":"D Zhang","year":"2023","unstructured":"Zhang, D., Shen, Z., Li, Y.: Requirement analysis and service optimization of multiple category fresh products in online retailing using importance-Kano analysis. J. Retail. Consum. Serv. 72, 103253 (2023). https:\/\/doi.org\/10.1016\/j.jretconser.2022.103253","journal-title":"J. Retail. Consum. Serv."},{"key":"1798_CR28","doi-asserted-by":"publisher","first-page":"7068","DOI":"10.1080\/00207543.2019.1574989","volume":"57","author":"JW Bi","year":"2019","unstructured":"Bi, J.W., Liu, Y., Fan, Z.P., Cambria, E.: Modelling customer satisfaction from online reviews using ensemble neural network and effect-based Kano model. Int. J. Prod. Res. 57, 7068\u20137088 (2019). https:\/\/doi.org\/10.1080\/00207543.2019.1574989","journal-title":"Int. J. Prod. Res."},{"key":"1798_CR29","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.ijinfomgt.2018.11.004","volume":"46","author":"A Mart\u00ed Bigorra","year":"2019","unstructured":"Mart\u00ed Bigorra, A., Isaksson, O., Karlberg, M.: Aspect-based Kano categorization. Int J Inform Manage. 46, 163\u2013172 (2019). https:\/\/doi.org\/10.1016\/j.ijinfomgt.2018.11.004","journal-title":"Int J Inform Manage."},{"key":"1798_CR30","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.engappai.2015.12.005","volume":"49","author":"J Jin","year":"2016","unstructured":"Jin, J., Ji, P., Gu, R.: Identifying comparative customer requirements from product online reviews for competitor analysis. Eng. Appl. Artif. Intel. 49, 61\u201373 (2016). https:\/\/doi.org\/10.1016\/j.engappai.2015.12.005","journal-title":"Eng. Appl. Artif. Intel."},{"key":"1798_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2020.113467","volume":"142","author":"X Xu","year":"2021","unstructured":"Xu, X.: What are customers commenting on, and how is their satisfaction affected? Examining online reviews in the on-demand food service context. Decis. Support. Syst. 142, 113467 (2021). https:\/\/doi.org\/10.1016\/j.dss.2020.113467","journal-title":"Decis. Support. Syst."},{"key":"1798_CR32","doi-asserted-by":"publisher","DOI":"10.1108\/K-05-2023-0850","author":"D Zhao","year":"2023","unstructured":"Zhao, D., Tang, Z., Sun, F.: Research on the weak demand signal identification model of innovative product based on domain ontology construction. Kybernetes (2023). https:\/\/doi.org\/10.1108\/K-05-2023-0850","journal-title":"Kybernetes"},{"key":"1798_CR33","doi-asserted-by":"publisher","first-page":"102030","DOI":"10.1016\/j.jretconser.2019.102030","volume":"54","author":"J Pallant","year":"2020","unstructured":"Pallant, J., Sands, S., Karpen, I.: Product customization: a profile of consumer demand. J Retail Consum Serv. 54, 102030 (2020). https:\/\/doi.org\/10.1016\/j.jretconser.2019.102030","journal-title":"J Retail Consum Serv."},{"key":"1798_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.jretconser.2023.103409","volume":"74","author":"DY Kim","year":"2023","unstructured":"Kim, D.Y., Kim, S.Y.: Investigating the effect of customer-generated content on performance in online platform-based experience goods market. J. Retail. Consum. Serv. 74, 103409 (2023). https:\/\/doi.org\/10.1016\/j.jretconser.2023.103409","journal-title":"J. Retail. Consum. Serv."},{"key":"1798_CR35","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1142\/S0219622023500244","volume":"23","author":"YJ Chen","year":"2023","unstructured":"Chen, Y.J., Chen, Y.M.: Online information-based product evolution course mining and prediction. Int J Inf Tech Decis. 23, 599\u2013627 (2023). https:\/\/doi.org\/10.1142\/S0219622023500244","journal-title":"Int J Inf Tech Decis."},{"key":"1798_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2023.101996","volume":"57","author":"K Zhang","year":"2023","unstructured":"Zhang, K., Lin, K.Y., Wang, J., Ma, Y., Li, H., Zhang, L., Liu, K., Feng, L.: UNISON framework for user requirement elicitation and classification of smart product-service system. Adv. Eng. Inform. 57, 101996 (2023). https:\/\/doi.org\/10.1016\/j.aei.2023.101996","journal-title":"Adv. Eng. Inform."},{"key":"1798_CR37","doi-asserted-by":"publisher","first-page":"19219","DOI":"10.1007\/S11042-023-16158-3\/FIGURES\/17","volume":"83","author":"P Chauhan","year":"2024","unstructured":"Chauhan, P., Sharma, N., Sikka, G.: On the importance of pre-processing in small-scale analyses of twitter: a case study of the 2019 Indian general election. Multimed Tools Appl. 83, 19219\u201319258 (2024). https:\/\/doi.org\/10.1007\/S11042-023-16158-3\/FIGURES\/17","journal-title":"Multimed Tools Appl."},{"key":"1798_CR38","doi-asserted-by":"publisher","DOI":"10.3389\/FSOC.2022.886498\/BIBTEX","volume":"7","author":"R Egger","year":"2022","unstructured":"Egger, R., Yu, J.: A topic modeling comparison between LDA, NMF, Top2Vec, and BERTopic to demystify twitter posts. Front. Sociol. 7, 886498 (2022). https:\/\/doi.org\/10.3389\/FSOC.2022.886498\/BIBTEX","journal-title":"Front. Sociol."},{"key":"1798_CR39","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1038\/s41746-023-00862-3","volume":"6","author":"M Uncovska","year":"2023","unstructured":"Uncovska, M., Freitag, B., Meister, S., Medicine, L.F.-N.D.: Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany. Npj Digit Med. 6, 115 (2023). https:\/\/doi.org\/10.1038\/s41746-023-00862-3","journal-title":"Npj Digit Med."},{"key":"1798_CR40","doi-asserted-by":"publisher","first-page":"9932","DOI":"10.1109\/TKDE.2022.3219231","volume":"35","author":"M Saaki","year":"2023","unstructured":"Saaki, M., Hosseini, S., Rahmani, S., Kangavari, M.R., Hua, W., Zhou, X.: Value-wise convnet for transformer models: an infinite time-aware recommender system. IEEE T Knowl Data En. 35, 9932\u20139945 (2023). https:\/\/doi.org\/10.1109\/TKDE.2022.3219231","journal-title":"IEEE T Knowl Data En."},{"key":"1798_CR41","doi-asserted-by":"publisher","first-page":"2003","DOI":"10.1007\/S11280-022-01108-0","volume":"26","author":"T Zhu","year":"2023","unstructured":"Zhu, T., Hua, W., Qu, J., Hosseini, S., Zhou, X.: Auto-regressive extractive summarization with replacement. World Wide Web. 26, 2003\u20132026 (2023). https:\/\/doi.org\/10.1007\/S11280-022-01108-0","journal-title":"World Wide Web."},{"key":"1798_CR42","doi-asserted-by":"publisher","first-page":"2591","DOI":"10.1145\/3543507.3583317","volume":"2023","author":"Y Liu","year":"2023","unstructured":"Liu, Y., Hua, W., Xin, K., Hosseini, S., Zhou, X.: TEA: time-aware entity alignment in knowledge graphs. Proc ACM Web Conf 2023, 2591\u20132599 (2023). https:\/\/doi.org\/10.1145\/3543507.3583317","journal-title":"Proc ACM Web Conf"},{"key":"1798_CR43","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1007\/s10664-023-10348-1","volume":"28","author":"Y Chen","year":"2023","unstructured":"Chen, Y., Fernandes, E., Adams, B., Hassan, A.E.: On practitioners\u2019 concerns when adopting service mesh frameworks. Empir Softw Eng. 28, 113 (2023). https:\/\/doi.org\/10.1007\/s10664-023-10348-1","journal-title":"Empir Softw Eng."},{"key":"1798_CR44","doi-asserted-by":"publisher","first-page":"19885","DOI":"10.1007\/s00521-023-08827-z","volume":"35","author":"T Mahmood","year":"2023","unstructured":"Mahmood, T., Naseem, S., Ashraf, R., Asif, M., Umair, M., Shah, M.: Recognizing factors effecting the use of mobile banking apps through sentiment and thematic analysis on user reviews. Neural Comput. Appl. 35, 19885\u201319897 (2023). https:\/\/doi.org\/10.1007\/s00521-023-08827-z","journal-title":"Neural Comput. Appl."},{"key":"1798_CR45","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1073\/pnas.2117292119","volume":"119","author":"PC Sukhwal","year":"2022","unstructured":"Sukhwal, P.C., Kankanhalli, A.: Determining containment policy impacts on public sentiment during the pandemic using social media data. Proc. Natl. Acad. Sci. 119, 1\u20138 (2022). https:\/\/doi.org\/10.1073\/pnas.2117292119","journal-title":"Proc. Natl. Acad. Sci."},{"key":"1798_CR46","doi-asserted-by":"publisher","DOI":"10.1016\/j.techfore.2022.122130","volume":"186","author":"E Jeon","year":"2023","unstructured":"Jeon, E., Yoon, N., Sohn, S.Y.: Exploring new digital therapeutics technologies for psychiatric disorders using BERTopic and PatentSBERTa. Technol Forecast Soc. 186, 122130 (2023). https:\/\/doi.org\/10.1016\/j.techfore.2022.122130","journal-title":"Technol Forecast Soc."},{"key":"1798_CR47","doi-asserted-by":"publisher","first-page":"120888","DOI":"10.1016\/j.eswa.2023.120888","volume":"233","author":"M Abdelhakim","year":"2023","unstructured":"Abdelhakim, M., Liu, B., Sun, C.: Ar-PuFi: a short-text dataset to identify the offensive messages towards public figures in the Arabian community. Expert Syst Appl. 233, 120888 (2023). https:\/\/doi.org\/10.1016\/j.eswa.2023.120888","journal-title":"Expert Syst Appl."},{"key":"1798_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.amc.2023.128276","volume":"459","author":"Q Zhang","year":"2023","unstructured":"Zhang, Q., Tang, R., Yao, Z., Zhang, Z.B.: A parallel PageRank algorithm for undirected graph. Appl. Math. Comput. 459, 128276 (2023). https:\/\/doi.org\/10.1016\/j.amc.2023.128276","journal-title":"Appl. Math. Comput."},{"key":"1798_CR49","doi-asserted-by":"crossref","unstructured":"Chen, X., Nie, F., Huang, J. Z., Yang, M.: Scalable normalized cut with improved spectral rotation. Int. Joint Conf. Artif. Intell. pp 1518\u20131524.   https:\/\/www.ijcai.org\/Proceedings\/2017\/0210.pdf (2017). Accessed 18 Jan 2024","DOI":"10.24963\/ijcai.2017\/210"},{"key":"1798_CR50","doi-asserted-by":"publisher","unstructured":"Grootendorst, M.: BERTopic: Neural topic modeling with a class-based TF-IDF procedure. ArXiv https:\/\/doi.org\/10.48550\/arXiv.2203.05794 (2022). Accessed 18 Jan 2024","DOI":"10.48550\/arXiv.2203.05794"},{"key":"1798_CR51","doi-asserted-by":"publisher","first-page":"1030","DOI":"10.1016\/j.ins.2022.07.126","volume":"609","author":"T Zhou","year":"2022","unstructured":"Zhou, T., Law, K., Creighton, D.: A weakly-supervised graph-based joint sentiment topic model for multi-topic sentiment analysis. Inf Sci (N Y). 609, 1030\u20131051 (2022). https:\/\/doi.org\/10.1016\/j.ins.2022.07.126","journal-title":"Inf Sci (N Y)."},{"key":"1798_CR52","doi-asserted-by":"publisher","DOI":"10.1016\/J.IS.2022.102131","volume":"112","author":"A Abdelrazek","year":"2023","unstructured":"Abdelrazek, A., Eid, Y., Gawish, E., Medhat, W., Hassan, A.: Topic modeling algorithms and applications: a survey. Inf. Syst. 112, 102131 (2023). https:\/\/doi.org\/10.1016\/J.IS.2022.102131","journal-title":"Inf. Syst."},{"key":"1798_CR53","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1016\/j.jmse.2023.03.001","volume":"8","author":"M Zhang","year":"2023","unstructured":"Zhang, M., Sun, L., Li, Y., Wang, G.A., He, Z.: Using supplementary reviews to improve customer requirement identification and product design development. J Manage Sci Eng. 8, 584\u2013597 (2023). https:\/\/doi.org\/10.1016\/j.jmse.2023.03.001","journal-title":"J Manage Sci Eng."},{"key":"1798_CR54","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2023.119155","volume":"642","author":"D He","year":"2023","unstructured":"He, D., Tang, Z., Chen, Q., Han, Z., Zhao, D., Sun, F.: A two-stage deep graph clustering method for identifying the evolutionary patterns of the time series of animation view counts. Inf Sci (N Y). 642, 119155 (2023). https:\/\/doi.org\/10.1016\/j.ins.2023.119155","journal-title":"Inf Sci (N Y)."},{"key":"1798_CR55","doi-asserted-by":"publisher","first-page":"2528","DOI":"10.1108\/MD-03-2020-0320","volume":"59","author":"Z Tang","year":"2021","unstructured":"Tang, Z., Wang, T., Cui, J., Han, Z., He, B.: Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns. Manage Sci. 59, 2528\u20132548 (2021). https:\/\/doi.org\/10.1108\/MD-03-2020-0320","journal-title":"Manage Sci."},{"key":"1798_CR56","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121852","volume":"238","author":"G Sun","year":"2024","unstructured":"Sun, G., Cheng, Y., Zhang, Z., Tong, X., Chai, T.: Text classification with improved word embedding and adaptive segmentation. Expert Syst. Appl. 238, 121852 (2024). https:\/\/doi.org\/10.1016\/j.eswa.2023.121852","journal-title":"Expert Syst. Appl."},{"key":"1798_CR57","doi-asserted-by":"publisher","DOI":"10.1016\/j.jretconser.2023.103335","volume":"73","author":"AG Fernando","year":"2023","unstructured":"Fernando, A.G., Aw, E.C.X.: What do consumers want? A methodological framework to identify determinant product attributes from consumers\u2019 online questions. J. Retail. Consum. Serv. 73, 103335 (2023). https:\/\/doi.org\/10.1016\/j.jretconser.2023.103335","journal-title":"J. Retail. Consum. Serv."},{"key":"1798_CR58","doi-asserted-by":"publisher","DOI":"10.1016\/j.jretconser.2024.103780","volume":"79","author":"VH Luong","year":"2024","unstructured":"Luong, V.H., Tarquini, A., Anadol, Y., Klaus, P., Manthiou, A.: Is digital fashion the future of the metaverse? Insights from YouTube comments. J. Retail. Consum. Serv. 79, 103780 (2024). https:\/\/doi.org\/10.1016\/j.jretconser.2024.103780","journal-title":"J. Retail. Consum. Serv."}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-025-01798-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00530-025-01798-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-025-01798-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T15:03:19Z","timestamp":1756998199000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00530-025-01798-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,5]]},"references-count":58,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["1798"],"URL":"https:\/\/doi.org\/10.1007\/s00530-025-01798-2","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"value":"0942-4962","type":"print"},{"value":"1432-1882","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,5]]},"assertion":[{"value":"30 June 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 April 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 May 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"228"}}