{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T19:04:50Z","timestamp":1772823890406,"version":"3.50.1"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T00:00:00Z","timestamp":1702512000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T00:00:00Z","timestamp":1702512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2024,5]]},"DOI":"10.1007\/s11227-023-05783-2","type":"journal-article","created":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T05:02:19Z","timestamp":1702530139000},"page":"9687-9712","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Topic Mapping-based framework to analyze textual risk reports from social media big data contents"],"prefix":"10.1007","volume":"80","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1694-2660","authenticated-orcid":false,"given":"Mohammadreza","family":"Sheikhattar","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1953-5761","authenticated-orcid":false,"given":"Alireza","family":"Mansouri","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,12,14]]},"reference":[{"key":"5783_CR1","doi-asserted-by":"crossref","unstructured":"Abramowicz W, Kaczmarek T, Kowalkiewicz M (2004) Automatic topic map creation using term crawling and clustering hierarchy projection. In: Constructing the Infrastructure for the Knowledge Economy (pp. 555\u2013567). Springer.","DOI":"10.1007\/978-1-4757-4852-9_42"},{"issue":"1","key":"5783_CR2","first-page":"61","volume":"3","author":"ASS Balaid","year":"2013","unstructured":"Balaid ASS, Zibarzani M, Rozan MZA (2013) A comprehensive review of knowledge mapping techniques. J Inf Syst Res Innov 3(1):61\u201366","journal-title":"J Inf Syst Res Innov"},{"issue":"1","key":"5783_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3745\/JIPS.2013.9.1.001","volume":"9","author":"M Brahami","year":"2013","unstructured":"Brahami M, Atmani B, Matta N (2013) Dynamic knowledge mapping guided by data mining: application on healthcare. J Inf Process Syst 9(1):1\u201330","journal-title":"J Inf Process Syst"},{"issue":"1","key":"5783_CR4","first-page":"2","volume":"1","author":"S Dieb","year":"2021","unstructured":"Dieb S, Amano K, Tanabe K, Sato D, Ishii M, Tanifuji M (2021) Creating research topic map for NIMS SAMURAI database using natural language processing approach. Sci Technol Adv Mater: Methods 1(1):2\u201311","journal-title":"Sci Technol Adv Mater: Methods"},{"key":"5783_CR5","doi-asserted-by":"crossref","unstructured":"Ding Z, Liu R, Yuan H (2021) A text mining-based thematic model for analyzing construction and demolition waste management studies. Environ Sci Pollut Res, 1\u201329","DOI":"10.1007\/s11356-021-13989-1"},{"key":"5783_CR6","doi-asserted-by":"crossref","unstructured":"Driessen S, Huijsen WO, Grootveld M (2007) A framework for evaluating knowledge\u2010mapping tools. J Knowl Manag","DOI":"10.1108\/13673270710738960"},{"key":"5783_CR7","unstructured":"Hatzigaidas A, Papastergiou A, Tryfon G, Maritsa D (2004) Topic map existing tools: a brief review. Paper presented at the ICTAMI 2004 (International Conference on Theory and Applications of Mathematics and Informatics)"},{"key":"5783_CR8","unstructured":"Hsieh P-J (2021) Determinants of knowledge-sharing intentions for shared decision-making platforms. J Comput Inf Syst, 1\u201312"},{"key":"5783_CR9","doi-asserted-by":"crossref","unstructured":"Huang C-H, Yin J, Hou F (2011) A text similarity measurement combining word semantic information with TF-IDF method. Jisuanji Xuebao (Chin J Comput) 34(5):856\u2013864","DOI":"10.3724\/SP.J.1016.2011.00856"},{"issue":"3","key":"5783_CR10","first-page":"463","volume":"62","author":"H Jiang","year":"2022","unstructured":"Jiang H, Chen C (2022) Data science skills and graduate certificates: a quantitative text analysis. J Comput Inf Syst 62(3):463\u2013479","journal-title":"J Comput Inf Syst"},{"key":"5783_CR11","doi-asserted-by":"publisher","first-page":"105570","DOI":"10.1016\/j.cie.2018.12.017","volume":"139","author":"ME Kara","year":"2020","unstructured":"Kara ME, F\u0131rat S\u00dcO, Ghadge A (2020) A data mining-based framework for supply chain risk management. Comput Ind Eng 139:105570","journal-title":"Comput Ind Eng"},{"key":"5783_CR12","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.techfore.2016.10.017","volume":"116","author":"V Kayser","year":"2017","unstructured":"Kayser V, Blind K (2017) Extending the knowledge base of foresight: The contribution of text mining. Technol Forecast Soc Chang 116:208\u2013215","journal-title":"Technol Forecast Soc Chang"},{"key":"5783_CR13","doi-asserted-by":"publisher","first-page":"104873","DOI":"10.1016\/j.ssci.2020.104873","volume":"130","author":"D Kurian","year":"2020","unstructured":"Kurian D, Sattari F, Lefsrud L, Ma Y (2020) Using machine learning and keyword analysis to analyze incidents and reduce risk in oil sands operations. Saf Sci 130:104873","journal-title":"Saf Sci"},{"key":"5783_CR14","doi-asserted-by":"crossref","unstructured":"Lampridis O, Vakali A (2021) A Human-centric explainable approach for fake news spreading detection","DOI":"10.1007\/s00607-021-01013-w"},{"issue":"8","key":"5783_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10916-018-1003-9","volume":"42","author":"K Lan","year":"2018","unstructured":"Lan K, Wang D-T, Fong S, Liu L-S, Wong KK, Dey N (2018) A survey of data mining and deep learning in bioinformatics. J Med Syst 42(8):1\u201320","journal-title":"J Med Syst"},{"issue":"2","key":"5783_CR16","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1007\/s11192-018-2905-5","volume":"117","author":"S Li","year":"2018","unstructured":"Li S, Hu J, Cui Y, Hu J (2018) DeepPatent: patent classification with convolutional neural networks and word embedding. Scientometrics 117(2):721\u2013744","journal-title":"Scientometrics"},{"issue":"3","key":"5783_CR17","first-page":"609","volume":"62","author":"C Liu","year":"2022","unstructured":"Liu C, Ji H, Wei J (2022) Smart supply chain risk assessment in intelligent manufacturing. J Comput Inf Syst 62(3):609\u2013621","journal-title":"J Comput Inf Syst"},{"key":"5783_CR18","doi-asserted-by":"publisher","first-page":"103154","DOI":"10.1016\/j.compind.2019.103154","volume":"115","author":"L Liu","year":"2020","unstructured":"Liu L, Li Y, Xiong Y, Cavallucci D (2020) A new function-based patent knowledge retrieval tool for conceptual design of innovative products. Comput Ind 115:103154","journal-title":"Comput Ind"},{"key":"5783_CR19","doi-asserted-by":"crossref","unstructured":"Mansouri A, Taghiyareh F (2020) Phase transition in the social impact model of opinion formation in scale-free networks: the social power effect. J Artif Soc Soc Simul 23(2)","DOI":"10.18564\/jasss.4232"},{"issue":"33","key":"5783_CR20","first-page":"1","volume":"1","author":"A Mansouri","year":"2021","unstructured":"Mansouri A, Taghiyareh F (2021) Phase transition in the social impact model of opinion formation in log-normal networks. J Inf Syst Telecommun 1(33):1","journal-title":"J Inf Syst Telecommun"},{"issue":"2","key":"5783_CR21","first-page":"34","volume":"1","author":"A Mansouri","year":"2018","unstructured":"Mansouri A, Taghiyareh F, Hatami J (2018) Post-based prediction of users\u2019 opinions employing the social impact model improved by emotion. Int J Web Res 1(2):34\u201342","journal-title":"Int J Web Res"},{"key":"5783_CR22","doi-asserted-by":"crossref","unstructured":"Mansouri A, Taghiyareh F, Hatami J (2019) Improving opinion formation models on social media through emotions. Paper presented at the 2019 5th International Conference on Web Research (ICWR)","DOI":"10.1109\/ICWR.2019.8765288"},{"key":"5783_CR23","unstructured":"Mimno D, Wallach H, Talley E, Leenders M, McCallum A (2011) Optimizing semantic coherence in topic models. Paper presented at the proceedings of the 2011 conference on empirical methods in natural language processing"},{"key":"5783_CR24","doi-asserted-by":"crossref","unstructured":"Mohammed MA, Ghani MKA, Arunkumar N, Hamed RI, Mostafa SA, Abdullah MK, Burhanuddin M (2022) Retraction Note: Decision support system for nasopharyngeal carcinoma discrimination from endoscopic images using artificial neural network. Springer","DOI":"10.1007\/s11227-022-04871-z"},{"issue":"4","key":"5783_CR25","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1016\/j.dss.2004.03.008","volume":"39","author":"T-H Ong","year":"2005","unstructured":"Ong T-H, Chen H, Sung W-K, Zhu B (2005) Newsmap: a knowledge map for online news. Decis Support Syst 39(4):583\u2013597","journal-title":"Decis Support Syst"},{"key":"5783_CR26","doi-asserted-by":"crossref","unstructured":"Razali N, Mostafa SA, Mustapha A, Abd Wahab MH, Ibrahim NA (2020) Risk factors of cervical cancer using classification in data mining. Paper presented at the Journal of Physics: Conference Series","DOI":"10.1088\/1742-6596\/1529\/2\/022102"},{"key":"5783_CR27","doi-asserted-by":"crossref","unstructured":"Seilsepour A, Ravanmehr R, Nassiri R (2023) Topic sentiment analysis based on deep neural network using document embedding technique. J Supercomput, 1\u201339","DOI":"10.1142\/S0219622023500736"},{"issue":"5","key":"5783_CR28","doi-asserted-by":"publisher","first-page":"2323","DOI":"10.3390\/app11052323","volume":"11","author":"SM Shah","year":"2021","unstructured":"Shah SM, L\u00fctjen M, Freitag M (2021) Text mining for supply chain risk management in the apparel industry. Appl Sci 11(5):2323","journal-title":"Appl Sci"},{"issue":"5","key":"5783_CR29","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1016\/j.ipm.2006.11.011","volume":"43","author":"Y-H Tseng","year":"2007","unstructured":"Tseng Y-H, Lin C-J, Lin Y-I (2007) Text mining techniques for patent analysis. Inf Process Manage 43(5):1216\u20131247","journal-title":"Inf Process Manage"},{"issue":"2","key":"5783_CR30","doi-asserted-by":"publisher","first-page":"1033","DOI":"10.1007\/s11192-017-2299-9","volume":"111","author":"T Velden","year":"2017","unstructured":"Velden T, Yan S, Lagoze C (2017) Mapping the cognitive structure of astrophysics by infomap clustering of the citation network and topic affinity analysis. Scientometrics 111(2):1033\u20131051","journal-title":"Scientometrics"},{"issue":"1","key":"5783_CR31","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1080\/13658816.2017.1367003","volume":"32","author":"Z Wang","year":"2018","unstructured":"Wang Z, Ye X (2018) Social media analytics for natural disaster management. Int J Geogr Inf Sci 32(1):49\u201372","journal-title":"Int J Geogr Inf Sci"},{"issue":"3","key":"5783_CR32","doi-asserted-by":"publisher","first-page":"1519","DOI":"10.1111\/acfi.12453","volume":"59","author":"L Wei","year":"2019","unstructured":"Wei L, Li G, Zhu X, Li J (2019) Discovering bank risk factors from financial statements based on a new semi-supervised text mining algorithm. Account Finance 59(3):1519\u20131552","journal-title":"Account Finance"},{"key":"5783_CR33","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1016\/j.eneco.2019.01.020","volume":"80","author":"L Wei","year":"2019","unstructured":"Wei L, Li G, Zhu X, Sun X, Li J (2019) Developing a hierarchical system for energy corporate risk factors based on textual risk disclosures. Energy Econ 80:452\u2013460","journal-title":"Energy Econ"},{"key":"5783_CR34","doi-asserted-by":"crossref","unstructured":"Wu Y, Dunaway DJ (2013) Creating a large topic map by integrating Wandora and Ontopia. Library hi tech","DOI":"10.1108\/07378831311303930"},{"issue":"2","key":"5783_CR35","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1108\/IMDS-06-2020-0325","volume":"121","author":"H Ying","year":"2020","unstructured":"Ying H, Chen L, Zhao X (2020) Application of text mining in identifying the factors of supply chain financing risk management. Ind Manag Data Syst 121(2):498\u2013518","journal-title":"Ind Manag Data Syst"},{"issue":"01","key":"5783_CR36","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1142\/S0219622021500516","volume":"21","author":"A Yosef","year":"2022","unstructured":"Yosef A, Schneider M, Shnaider E (2022) Data mining method for identifying biased or misleading future outlook. Int J Inf Technol Decis Mak 21(01):109\u2013141","journal-title":"Int J Inf Technol Decis Mak"},{"key":"5783_CR37","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1016\/j.knosys.2017.03.009","volume":"124","author":"H Zhou","year":"2017","unstructured":"Zhou H, Yu H, Hu R, Hu J (2017) A survey on trends of cross-media topic evolution map. Knowl-Based Syst 124:164\u2013175","journal-title":"Knowl-Based Syst"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05783-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-023-05783-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05783-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,18]],"date-time":"2024-04-18T13:31:44Z","timestamp":1713447104000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-023-05783-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,14]]},"references-count":37,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2024,5]]}},"alternative-id":["5783"],"URL":"https:\/\/doi.org\/10.1007\/s11227-023-05783-2","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,14]]},"assertion":[{"value":"3 November 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 December 2023","order":2,"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 that they have no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}