Unveiling trends: a comprehensive analysis of state funded projects of Türkiye through content analysis and text mining

Talha Koruk; Turgay Tugay Bilgin

Article Details

Unveiling trends: a comprehensive analysis of state funded projects of Türkiye through content analysis and text mining

Authors:

Talha Koruk | Turgay Tugay Bilgin

Publisher:

Murat YAKAR

Main Topics:

Information Modelling | Management and Ontologies

Journal:

Turkish Journal of Engineering Vol.9 Issue 2, pp.237-249

Document Type:

Article

Publication Date:

6/2025

Document Language:

English

Document ID (Org No.):

2001339340

pISSN:

2587-1366

Keywords:

Abstract:

 This paper presents a comprehensive analysis of 12,724 projects approved by TUBITAK The Scientific and Technological Research Council of Türkiye between 2008 and 2022. The research employs advanced text mining techniques, including N-gram-based text categorization, TF-IDF, and PMI scores, to uncover trends in research and development activities in Türkiye. The analysis begins by examining the distribution of projects across years and regions, then focuses on five leading sectors: Information Technologies, Automotive, Machinery Manufacturing, Electrical-Electronics, and Defense Industry. The study identifies prominent themes and their evolution over time for each sector, thereby illuminating the dynamics of Türkiyes innovation ecosystem. The results highlight sector-specific trends as well as cross-sector common themes such as artificial intelligence, mobile applications, and sustainable technologies. This research provides valuable insights for policymakers, researchers, and industry stakeholders in shaping Türkiyes scientific and technological development. By leveraging text mining techniques on a large corpus of project data, the study offers a data-driven perspective on the changing landscape of innovation in Türkiye, contributing to a better understanding of national research priorities and emerging technological focus areas.

 This paper presents a comprehensive analysis of 12,724 projects approved by TUBITAK The Scientific and Technological Research Council of Türkiye between 2008 and 2022. The research employs advanced text mining techniques, including N-gram-based text categorization, TF-IDF, and PMI scores, to uncover trends in research and development activities in Türkiye. The analysis begins by examining the distribution of projects across years and regions, then focuses on five leading sectors: Information Technologies, Automotive, Machinery Manufacturing, Electrical-Electronics, and Defense Industry. The study identifies prominent themes and their evolution over time for each sector, thereby illuminating the dynamics of Türkiyes innovation ecosystem. The results highlight sector-specific trends as well as cross-sector common themes such as artificial intelligence, mobile applications, and sustainable technologies. This research provides valuable insights for policymakers, researchers, and industry stakeholders in shaping Türkiyes scientific and technological development. By leveraging text mining techniques on a large corpus of project data, the study offers a data-driven perspective on the changing landscape of innovation in Türkiye, contributing to a better understanding of national research priorities and emerging technological focus areas.

 This paper presents a comprehensive analysis of 12,724 projects approved by TUBITAK The Scientific and Technological Research Council of Türkiye between 2008 and 2022. The research employs advanced text mining techniques, including N-gram-based text categorization, TF-IDF, and PMI scores, to uncover trends in research and development activities in Türkiye. The analysis begins by examining the distribution of projects across years and regions, then focuses on five leading sectors: Information Technologies, Automotive, Machinery Manufacturing, Electrical-Electronics, and Defense Industry. The study identifies prominent themes and their evolution over time for each sector, thereby illuminating the dynamics of Türkiyes innovation ecosystem. The results highlight sector-specific trends as well as cross-sector common themes such as artificial intelligence, mobile applications, and sustainable technologies. This research provides valuable insights for policymakers, researchers, and industry stakeholders in shaping Türkiyes scientific and technological development. By leveraging text mining techniques on a large corpus of project data, the study offers a data-driven perspective on the changing landscape of innovation in Türkiye, contributing to a better understanding of national research priorities and emerging technological focus areas.

 This paper presents a comprehensive analysis of 12,724 projects approved by TUBITAK The Scientific and Technological Research Council of Türkiye between 2008 and 2022. The research employs advanced text mining techniques, including N-gram-based text categorization, TF-IDF, and PMI scores, to uncover trends in research and development activities in Türkiye. The analysis begins by examining the distribution of projects across years and regions, then focuses on five leading sectors: Information Technologies, Automotive, Machinery Manufacturing, Electrical-Electronics, and Defense Industry. The study identifies prominent themes and their evolution over time for each sector, thereby illuminating the dynamics of Türkiyes innovation ecosystem. The results highlight sector-specific trends as well as cross-sector common themes such as artificial intelligence, mobile applications, and sustainable technologies. This research provides valuable insights for policymakers, researchers, and industry stakeholders in shaping Türkiyes scientific and technological development. By leveraging text mining techniques on a large corpus of project data, the study offers a data-driven perspective on the changing landscape of innovation in Türkiye, contributing to a better understanding of national research priorities and emerging technological focus areas.

Article Details

Unveiling trends: a comprehensive analysis of state funded projects of Türkiye through content analysis and text mining

Authors:

Talha Koruk | Turgay Tugay Bilgin

Publisher:

Murat YAKAR

Main Topics:

Information Modelling | Management and Ontologies

Journal:

Turkish Journal of Engineering Vol.9 Issue 2, pp.237-249

Document Type:

Article

Publication Date:

6/2025

Document Language:

English

Document ID (Org No.):

2001339340

pISSN:

2587-1366

Text mining

N-grams

TF-IDF

Research Trends

Innovation Analysis

Issues

Article Details

Unveiling trends: a comprehensive analysis of state funded projects of Türkiye through content analysis and text mining

Authors: Talha Koruk | Turgay Tugay Bilgin

Publisher: Murat YAKAR

Main Topics: Information Modelling | Management and Ontologies

Journal: Turkish Journal of Engineering Vol.9 Issue 2, pp.237-249

Document Type: Article

Publication Date: 6/2025

Document Language: English

Document ID (Org No.): 2001339340

pISSN: 2587-1366

Text mining

N-grams

TF-IDF

Research Trends

Innovation Analysis

Issues

Authors:

Talha Koruk | Turgay Tugay Bilgin

Publisher:

Murat YAKAR

Main Topics:

Information Modelling | Management and Ontologies

Journal:

Turkish Journal of Engineering Vol.9 Issue 2, pp.237-249

Document Type:

Article

Publication Date:

6/2025

Document Language:

English

Document ID (Org No.):

2001339340

pISSN:

2587-1366