[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122270-en":3,"doc-seo-122270-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122270,1099514067415,"Rowan","https://ap-avatar.wpscdn.com/avatar/100002539d78ffe74a7?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779092875211072502",8,"Research & Report","Bibliometric Analysis and the Use of Machine Learning for Identifying Latent Topics in ICT Research - Bachelor’s Thesis","Research addresses the challenge of navigating a large body of Finnish ICT publications by combining bibliometric mapping with unsupervised machine learning. The study conducts bibliometric analysis and discovers latent topics in Finnish ICT research to help stakeholders understand the field’s structure and evolution. Data are retrieved from the Scopus database via keyword search, yielding 19,500 records from 2005–2025. Visual mapping is performed with VOSviewer, and topic discovery uses BERTopic with the Llama 2 language model.","Bibliometric Analysis and the Use of Machine Learning for Identifying Latent Topics in ICT Research from Finland  \nAshim Acharya  \nBachelor’s thesis 06.2025  \nBachelor of Engineering in Information and Communication Technology  \nDescription  \nAcharya, Ashim  \nBibliometric analysis and the Use of Machine Learning for Identifying Latent topics in ICT Research from Finland  \nJyväskylä: Jamk University of Applied Sciences, May 2025, 46 pages  \nBachelor of Engineering in Information and Communication Technology. Bachelor’s thesis.  \nPermission for open access publication: Yes  \nLanguage of publication: English  \nAbstract  \nThis research was conducted regarding the complexity of navigating a massive volume of research output from Finland in the ICT sector. It aimed to identify and conduct a bibliometric analysis and uncover latent topics within Finnish ICT research so stakeholders can navigate its landscape meaningfully. Finnish Universities are popular and well-ranked internationally in their ICT research output. However, there is little indepth mapping of Finnish ICT research.  \nThus, with the primary objective of navigating the complex Finnish ICT research landscape, this research conducted a bibliometric analysis and an unsupervised machine learning with the latest BERTopic modeling technique. This study collected data from the Scopus database using a keyword search, which had 19500 records from 2005 to 2025 from Finnish ICT research. It carried out a bibliometric analysis at different levels with different units of analysis using VOSviewer software, followed by BERTopic modelling using Llama 2 language model.  \nFindings showed that in Finland, ICT researchers are collaborating frequently, while machine learning dominates, deep learning is an emerging topic, and sustainability is a key focus area. Regarding highly prominent authors, Mehdi Bennis tops the list, the United States has the most connections with Finland, and IEEE Access is a highly cited journal. Findings also showed the top 10 latent topics, which, despite being scattered, share some connection at a point. Interestingly, these topics are receiving fewer publications in 2025, signaling a shift in the focus of researchers. This study showed the value of combining bibliometric analysis with machine learning-based BERTopic modelling.  \nKeywords/tags (subjects)  \nBibliometric analysis, Machine Learning, BERTopic Modelling  \nConfidential information  \nThis research herby declares that it does not any confidential information.  \nContents  \n1 Introduction ................................................................................................................ 3  \n2 Research problems, objectives, and questions............................................................. 6  \n2.1 Research problem ............................................................................................................. 6  \n2.2 Research Objectives and Questions .................................................................................. 6  \n3 Research Method ........................................................................................................ 7  \n3.1 Data analysis...................................................................................................................... 8  \n3.2 Research Ethics and Reliability.......................................................................................... 8  \n~~4~~ Previous Knowledge Base ............................................................................................ 9  \n4.1 Bibliometric Analysis through VOS viewer........................................................................ 9  \n4.2 In-depth Understanding of the Use of Machine Learning .............................................. 11  \n4.2.1 Supervised Learning............................................................................................... 12  \n4.2.2 Unsupervised Learning ................................................","cbCaikWaOo6TBOVj","https://ap.wps.com/l/cbCaikWaOo6TBOVj","pdf",2654291,1,62,"English","en",105,"# Introduction\n# Research problems, objectives, and questions\n## Research problem\n## Research Objectives and Questions\n# Research Method\n## Data analysis\n## Research Ethics and Reliability\n# Previous Knowledge Base\n## Bibliometric Analysis through VOS viewer\n## In-depth Understanding of the Use of Machine Learning\n## Topic Modelling\n## BERTopic\n## LLaMA 2\n# Results\n## Bibliometric analysis from VOS Viewer\n## Co-authorship Analysis\n## Co-Occurrence analysis\n## Citation Analysis\n## Bibliographic coupling","[{\"question\":\"What is the main objective of the study?\",\"answer\":\"To map and analyze Finnish ICT research outputs and uncover latent topics using bibliometric analysis combined with machine learning, so stakeholders can navigate the research landscape meaningfully.\"},{\"question\":\"What data source and time range are used for the analysis?\",\"answer\":\"Records are collected from the Scopus database using a keyword search, covering 19,500 entries from 2005 to 2025 in Finnish ICT research.\"},{\"question\":\"How are latent topics identified in the study?\",\"answer\":\"Latent topics are discovered using BERTopic modeling with the Llama 2 language model after bibliometric mapping with VOSviewer.\"}]","Bibliometric Analysis and the Use of Machine Learning for Identifying Latent Topics in ICT Research - 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