Evaluating the latest trends of Industry 4.0 based on LDA topic model
| dc.contributor.author | Ozyurt, Ozcan | |
| dc.contributor.author | Özköse, Hakan | |
| dc.contributor.author | Ayaz, Ahmet | |
| dc.contributor.author | Özköse, Hakan | |
| dc.date.accessioned | 2025-10-18T13:24:30Z | |
| dc.date.created | 2024 | |
| dc.date.issued | 2024 | |
| dc.department | Fakülteler, İktisadi ve İdari Bilimler Fakültesi, Yönetim Bilişim Sistemleri Bölümü | |
| dc.description.abstract | This study employs the Latent Dirichlet allocation method, a topic modeling technique, to reveal hidden patterns in Industry 4.0 research. The dataset comprises 8584 articles published in the Scopus database from 2011 to the end of 2022. The analysis categorized the articles into 12 distinct topics. The three most prominent topics identified are Smart Cyber-Physical Systems, Digital Transformation and Knowledge Management and Data Science in Energy, respectively. The findings from this topic modeling provide a comprehensive overview for researchers in the field of Industry 4.0, offering valuable insights into current trends and potential future research directions. | |
| dc.description.sponsorship | Karadeniz Technical University | |
| dc.description.sponsorship | No Statement Available | |
| dc.identifier.doi | 10.1007/s11227-024-06247-x | |
| dc.identifier.endpage | 19030 | |
| dc.identifier.issn | 0920-8542 | |
| dc.identifier.issn | 1573-0484 | |
| dc.identifier.issue | 13 | |
| dc.identifier.orcid | Ayaz, Ahmet/0000-0003-1405-0546; | |
| dc.identifier.scopus | 2-s2.0-85194102071 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.startpage | 19003 | |
| dc.identifier.uri | https://doi.org/10.1007/s11227-024-06247-x | |
| dc.identifier.uri | https://hdl.handle.net/11772/22973 | |
| dc.identifier.volume | 80 | |
| dc.identifier.wos | WOS:001234050300004 | |
| dc.identifier.wosquality | Q2 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Springer | |
| dc.relation.ispartof | Journal of Supercomputing | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.relation.sdg | Goal-09: Industry Innovation And Infrastructure | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.snmz | WoS_20251016 | |
| dc.subject | Industry 4.0 | |
| dc.subject | Topic Modeling | |
| dc.subject | Latent Dirichlet Allocation | |
| dc.subject | Trend Analysis | |
| dc.subject | Text Mining | |
| dc.title | Evaluating the latest trends of Industry 4.0 based on LDA topic model | |
| dc.type | Article | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 7ad0a5ef-52d8-4ceb-bd14-e667561e441a | |
| relation.isAuthorOfPublication.latestForDiscovery | 7ad0a5ef-52d8-4ceb-bd14-e667561e441a |










