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

Year 2025, Volume: 9 Issue: 2, 237 - 249
https://doi.org/10.31127/tuje.1538068

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 Türkiye's 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 Türkiye's 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

References

  • Kaska, O., Akin, H. K., Tokgoz, N., & Halicioglu, R. (2017). An Analysis of TUBITAK Projects’ Budgets and Regional Distributions with Recommendations. Journal of Current Researches on Social Sciences, 7(1), 59-66.
  • Unutulmaz, S. (2022). TÜBİTAK Projelerindeki Güçlü Araştırma İşbirliğinin Sosyal Ağ Analizi ile Dinamiklerinin Değerlendirilmesi. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 13(35), 810-828.
  • Gurcan, F., & Cagiltay, N. E. (2023). Research trends on distance learning: A text mining-based literature review from 2008 to 2018. Interactive Learning Environments, 31(2), 1007-1028.
  • TÖNGEL, E., AYDIN, A., Mehmet, K. A. R. A., & ÇAKIR, R. (2020). “Bilgisayar ve Öğretim Teknolojileri” ve “Eğitim Teknolojileri” Alanlarında Yazılan Yüksek Lisans ve Doktora Tezlerinin Araştırma Eğilimleri: 2013-2018 Döneminin Bir Görüntüsü. Ondokuz Mayis University Journal of Education Faculty, 39(1), 69-82.
  • Gürbüz, T., & Uluyol, Ç. (2023). Research article classification with text mining method. Concurrency and Computation: Practice and Experience, 35(1), e7437.
  • Kukul, V., & Aydin, K. (2021). Classification of the theses and dissertations in the field of computer education and instructional technology in Turkey: An investigation through text mining. Participatory Educational Research, 8(1), 279-291.
  • Erdoğdu, F., & Gökoğlu, S. (2022). Bilgisayar ve Öğretim Teknolojileri Alanına İlişkin Kavramsal Eğilimin Sempozyum Bildirileri Çerçevesinde Belirlenmesi: Metin Madenciliği Yöntemi. Uludağ Üniversitesi Eğitim Fakültesi Dergisi, 35(3), 601-622.
  • Çalli, L., Çalli, F., & Çalli, B. A. (2021). Yönetim bilişim sistemleri disiplininde hazırlanan lisansüstü tezlerin gizli dirichlet ayrımı algoritmasıyla konu modellemesi. Manas Sosyal Araştırmalar Dergisi, 10(4), 2355-2372.
  • Moro, S., Cortez, P., & Rita, P. (2015). Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation. Expert Systems with Applications, 42(3), 1314-1324.
  • Bitzenbauer, P. (2021). Quantum physics education research over the last two decades: A bibliometric analysis. Education Sciences, 11(11), 699.
  • Hwang, G. J., & Fu, Q. K. (2019). Trends in the research design and application of mobile language learning: A review of 2007–2016 publications in selected SSCI journals. Interactive Learning Environments, 27(4), 567-581.
  • Karl, A., Wisnowski, J., & Rushing, W. H. (2015). A practical guide to text mining with topic extraction. Wiley Interdisciplinary Reviews: Computational Statistics, 7(5), 326-340.
  • Schonlau, M., Guenther, N., & Sucholutsky, I. (2017). Text mining with n-gram variables. The Stata Journal, 17(4), 866-881.
  • Loureiro, S. M. C., Guerreiro, J., & Ali, F. (2020). 20 years of research on virtual reality and augmented reality in tourism context: A text-mining approach. Tourism management, 77, 104028.
  • Hickman, L., Thapa, S., Tay, L., Cao, M., & Srinivasan, P. (2022). Text preprocessing for text mining in organizational research: Review and recommendations. Organizational Research Methods, 25(1), 114-146.
  • Al-Daihani, S. M., & Abrahams, A. (2016). A text mining analysis of academic libraries' tweets. The journal of academic librarianship, 42(2), 135-143.
  • Hsiao, Y. H., Chen, M. C., & Liao, W. C. (2017). Logistics service design for cross-border E-commerce using Kansei engineering with text-mining-based online content analysis. Telematics and Informatics, 34(4), 284-302.
  • Muataz Abdulwahid, M. ., Kurnaz, S., Kurnaz Türkben, A. ., Hayal, M. R., Elsayed, E. E. ., & Aslonqulovich Juraev, D. (2024). Inter-satellite optical wireless communication (Is-OWC) trends: a review, challenges and opportunities. Engineering Applications, 3(1), 1–15.
  • Akgül, V., Görmüş , K. S., Kutoğlu , Şenol H., & Jin, S. (2024). Performance analysis and kinematic test of the BeiDou Navigation Satellite System (BDS) over coastal waters of Türkiye. Advanced Engineering Science, 4, 1–14.
  • Aykır, D., Atalay, İ., & Coşkun, M. (2022). Periodic Changes of Temperature Extremes at Some Selected Stations in Turkiye (1970-2018). Coğrafya Dergisi, (45), 69-83.
  • Özen, M. (2018). Comparative study of regional crash data in Turkey. Turkish Journal of Engineering, 2(3), 113-118. https://doi.org/10.31127/tuje.385008
  • Yıldız, A. (2019). Predicting the energy production of a rooftop PV plant by using differential evolution algorithm. Turkish Journal of Engineering, 3(3), 106-109. https://doi.org/10.31127/tuje.466953
  • Aliyazıcıoğlu, K., Beker, F., Topaloğlu, R. H., Bilgilioğlu, B. B., & Çömert, R. (2021). Temporal monitoring of land use/land cover change in Kahramanmaraş city. Turkish Journal of Engineering, 5(3), 134-140. https://doi.org/10.31127/tuje.707156
  • Gündüz, F., & Zeybekoğlu, U. (2024). Analysis of temperature and precipitation series of Hirfanli Dam Basin by Mann Kendall, Spearman’s Rho and Innovative Trend Analysis. Turkish Journal of Engineering, 8(1), 11-19. https://doi.org/10.31127/tuje.1177522
  • Demirgül, T. ., Yılmaz, C. B. ., Zıpır, B. N. ., Kart, F. S. ., Pehriz, M. F. ., Demir, V. ., & Sevimli, M. F. . (2022). Investigation of Turkey’s climate periods in terms of precipitation and temperature changes. Engineering Applications, 1(1), 80–90.
  • Drahman, S. H., Maseri, H., Nap, M. C., & Hossen, Z. B. (2024). Twenty Years of Air Pollutant Index Trend Analysis in Kuching, Sarawak, Malaysia (2000-2019). Sains Malaysiana, 53(3), 623-633.
  • Çelik, Ş., & Köleoğlu, N. (2022). Trend analizi ve yapay sinir ağları: Tarımda bir uygulaması. Journal of Awareness, 7(1), 39-46.
  • Yao, Z., Chen, Y., Wang, J., Wu, S., Tu, Y., Zhao, M., & Zhang, L. (2021, December). Trend analysis neural networks for interpretable analysis of longitudinal data. In 2021 IEEE International Conference on Big Data (Big Data) (pp. 6061-6063). IEEE.
  • Sala, F. G., Osca-Lluch, J., & Peñaranda-Ortega, M. (2021). Evolution of scientific collaboration within Spanish Psychology between 1970 and 1989. Anales de psicología, 37(3), 589.
  • Negash, H., Legese, H., Adhanom, G., Mardu, F., Tesfay, K., Gebreslasie Gebremeskel, S., & Berhe, B. (2020). Six years trend analysis of tuberculosis in Northwestern Tigrai, Ethiopia; 2019: A retrospective study. Infection and Drug Resistance, 643-649.
  • İzgi, F., & Kavacık, M. (2024). Analyzing global competitiveness of Turkish air conditioning industry. Turkish Journal of Engineering, 8(2), 209-234.
  • Khan, A., & Ghosh, S. K. (2021). Student performance analysis and prediction in classroom learning: A review of educational data mining studies. Education and information technologies, 26, 205-240.
  • Leno, V., Polyvyanyy, A., Dumas, M., La Rosa, M., & Maggi, F. M. (2021). Robotic process mining: vision and challenges. Business & Information Systems Engineering, 63, 301-314.
  • Geyer-Klingeberg, J., Nakladal, J., Baldauf, F., & Veit, F. (2018). Process Mining and Robotic Process Automation: A Perfect Match. BPM (Dissertation/Demos/Industry), 2196, 124-131.
  • Vngrs-Ai. (n.d.). VNLP: State-of-the-art, lightweight NLP tools for Turkish language [Computer software]. GitHub. Retrieved from https://github.com/vngrs-ai/vnlp
  • Aizawa, A. (2003). An information-theoretic perspective of tf–idf measures. Information Processing & Management, 39(1), 45-65. https://doi.org/10.1016/S0306-4573(02)00021-3
  • Van de Cruys, T. (2011). Two multivariate generalizations of pointwise mutual information. In Proceedings of the Workshop on Distributional Semantics and Compositionality (pp. 16–20). Association for Computational Linguistics.
Year 2025, Volume: 9 Issue: 2, 237 - 249
https://doi.org/10.31127/tuje.1538068

Abstract

References

  • Kaska, O., Akin, H. K., Tokgoz, N., & Halicioglu, R. (2017). An Analysis of TUBITAK Projects’ Budgets and Regional Distributions with Recommendations. Journal of Current Researches on Social Sciences, 7(1), 59-66.
  • Unutulmaz, S. (2022). TÜBİTAK Projelerindeki Güçlü Araştırma İşbirliğinin Sosyal Ağ Analizi ile Dinamiklerinin Değerlendirilmesi. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 13(35), 810-828.
  • Gurcan, F., & Cagiltay, N. E. (2023). Research trends on distance learning: A text mining-based literature review from 2008 to 2018. Interactive Learning Environments, 31(2), 1007-1028.
  • TÖNGEL, E., AYDIN, A., Mehmet, K. A. R. A., & ÇAKIR, R. (2020). “Bilgisayar ve Öğretim Teknolojileri” ve “Eğitim Teknolojileri” Alanlarında Yazılan Yüksek Lisans ve Doktora Tezlerinin Araştırma Eğilimleri: 2013-2018 Döneminin Bir Görüntüsü. Ondokuz Mayis University Journal of Education Faculty, 39(1), 69-82.
  • Gürbüz, T., & Uluyol, Ç. (2023). Research article classification with text mining method. Concurrency and Computation: Practice and Experience, 35(1), e7437.
  • Kukul, V., & Aydin, K. (2021). Classification of the theses and dissertations in the field of computer education and instructional technology in Turkey: An investigation through text mining. Participatory Educational Research, 8(1), 279-291.
  • Erdoğdu, F., & Gökoğlu, S. (2022). Bilgisayar ve Öğretim Teknolojileri Alanına İlişkin Kavramsal Eğilimin Sempozyum Bildirileri Çerçevesinde Belirlenmesi: Metin Madenciliği Yöntemi. Uludağ Üniversitesi Eğitim Fakültesi Dergisi, 35(3), 601-622.
  • Çalli, L., Çalli, F., & Çalli, B. A. (2021). Yönetim bilişim sistemleri disiplininde hazırlanan lisansüstü tezlerin gizli dirichlet ayrımı algoritmasıyla konu modellemesi. Manas Sosyal Araştırmalar Dergisi, 10(4), 2355-2372.
  • Moro, S., Cortez, P., & Rita, P. (2015). Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation. Expert Systems with Applications, 42(3), 1314-1324.
  • Bitzenbauer, P. (2021). Quantum physics education research over the last two decades: A bibliometric analysis. Education Sciences, 11(11), 699.
  • Hwang, G. J., & Fu, Q. K. (2019). Trends in the research design and application of mobile language learning: A review of 2007–2016 publications in selected SSCI journals. Interactive Learning Environments, 27(4), 567-581.
  • Karl, A., Wisnowski, J., & Rushing, W. H. (2015). A practical guide to text mining with topic extraction. Wiley Interdisciplinary Reviews: Computational Statistics, 7(5), 326-340.
  • Schonlau, M., Guenther, N., & Sucholutsky, I. (2017). Text mining with n-gram variables. The Stata Journal, 17(4), 866-881.
  • Loureiro, S. M. C., Guerreiro, J., & Ali, F. (2020). 20 years of research on virtual reality and augmented reality in tourism context: A text-mining approach. Tourism management, 77, 104028.
  • Hickman, L., Thapa, S., Tay, L., Cao, M., & Srinivasan, P. (2022). Text preprocessing for text mining in organizational research: Review and recommendations. Organizational Research Methods, 25(1), 114-146.
  • Al-Daihani, S. M., & Abrahams, A. (2016). A text mining analysis of academic libraries' tweets. The journal of academic librarianship, 42(2), 135-143.
  • Hsiao, Y. H., Chen, M. C., & Liao, W. C. (2017). Logistics service design for cross-border E-commerce using Kansei engineering with text-mining-based online content analysis. Telematics and Informatics, 34(4), 284-302.
  • Muataz Abdulwahid, M. ., Kurnaz, S., Kurnaz Türkben, A. ., Hayal, M. R., Elsayed, E. E. ., & Aslonqulovich Juraev, D. (2024). Inter-satellite optical wireless communication (Is-OWC) trends: a review, challenges and opportunities. Engineering Applications, 3(1), 1–15.
  • Akgül, V., Görmüş , K. S., Kutoğlu , Şenol H., & Jin, S. (2024). Performance analysis and kinematic test of the BeiDou Navigation Satellite System (BDS) over coastal waters of Türkiye. Advanced Engineering Science, 4, 1–14.
  • Aykır, D., Atalay, İ., & Coşkun, M. (2022). Periodic Changes of Temperature Extremes at Some Selected Stations in Turkiye (1970-2018). Coğrafya Dergisi, (45), 69-83.
  • Özen, M. (2018). Comparative study of regional crash data in Turkey. Turkish Journal of Engineering, 2(3), 113-118. https://doi.org/10.31127/tuje.385008
  • Yıldız, A. (2019). Predicting the energy production of a rooftop PV plant by using differential evolution algorithm. Turkish Journal of Engineering, 3(3), 106-109. https://doi.org/10.31127/tuje.466953
  • Aliyazıcıoğlu, K., Beker, F., Topaloğlu, R. H., Bilgilioğlu, B. B., & Çömert, R. (2021). Temporal monitoring of land use/land cover change in Kahramanmaraş city. Turkish Journal of Engineering, 5(3), 134-140. https://doi.org/10.31127/tuje.707156
  • Gündüz, F., & Zeybekoğlu, U. (2024). Analysis of temperature and precipitation series of Hirfanli Dam Basin by Mann Kendall, Spearman’s Rho and Innovative Trend Analysis. Turkish Journal of Engineering, 8(1), 11-19. https://doi.org/10.31127/tuje.1177522
  • Demirgül, T. ., Yılmaz, C. B. ., Zıpır, B. N. ., Kart, F. S. ., Pehriz, M. F. ., Demir, V. ., & Sevimli, M. F. . (2022). Investigation of Turkey’s climate periods in terms of precipitation and temperature changes. Engineering Applications, 1(1), 80–90.
  • Drahman, S. H., Maseri, H., Nap, M. C., & Hossen, Z. B. (2024). Twenty Years of Air Pollutant Index Trend Analysis in Kuching, Sarawak, Malaysia (2000-2019). Sains Malaysiana, 53(3), 623-633.
  • Çelik, Ş., & Köleoğlu, N. (2022). Trend analizi ve yapay sinir ağları: Tarımda bir uygulaması. Journal of Awareness, 7(1), 39-46.
  • Yao, Z., Chen, Y., Wang, J., Wu, S., Tu, Y., Zhao, M., & Zhang, L. (2021, December). Trend analysis neural networks for interpretable analysis of longitudinal data. In 2021 IEEE International Conference on Big Data (Big Data) (pp. 6061-6063). IEEE.
  • Sala, F. G., Osca-Lluch, J., & Peñaranda-Ortega, M. (2021). Evolution of scientific collaboration within Spanish Psychology between 1970 and 1989. Anales de psicología, 37(3), 589.
  • Negash, H., Legese, H., Adhanom, G., Mardu, F., Tesfay, K., Gebreslasie Gebremeskel, S., & Berhe, B. (2020). Six years trend analysis of tuberculosis in Northwestern Tigrai, Ethiopia; 2019: A retrospective study. Infection and Drug Resistance, 643-649.
  • İzgi, F., & Kavacık, M. (2024). Analyzing global competitiveness of Turkish air conditioning industry. Turkish Journal of Engineering, 8(2), 209-234.
  • Khan, A., & Ghosh, S. K. (2021). Student performance analysis and prediction in classroom learning: A review of educational data mining studies. Education and information technologies, 26, 205-240.
  • Leno, V., Polyvyanyy, A., Dumas, M., La Rosa, M., & Maggi, F. M. (2021). Robotic process mining: vision and challenges. Business & Information Systems Engineering, 63, 301-314.
  • Geyer-Klingeberg, J., Nakladal, J., Baldauf, F., & Veit, F. (2018). Process Mining and Robotic Process Automation: A Perfect Match. BPM (Dissertation/Demos/Industry), 2196, 124-131.
  • Vngrs-Ai. (n.d.). VNLP: State-of-the-art, lightweight NLP tools for Turkish language [Computer software]. GitHub. Retrieved from https://github.com/vngrs-ai/vnlp
  • Aizawa, A. (2003). An information-theoretic perspective of tf–idf measures. Information Processing & Management, 39(1), 45-65. https://doi.org/10.1016/S0306-4573(02)00021-3
  • Van de Cruys, T. (2011). Two multivariate generalizations of pointwise mutual information. In Proceedings of the Workshop on Distributional Semantics and Compositionality (pp. 16–20). Association for Computational Linguistics.
There are 37 citations in total.

Details

Primary Language English
Subjects Information Modelling, Management and Ontologies
Journal Section Articles
Authors

Talha Koruk 0009-0008-8719-4763

Turgay Tugay Bilgin 0000-0002-9245-5728

Early Pub Date January 19, 2025
Publication Date
Submission Date August 24, 2024
Acceptance Date October 8, 2024
Published in Issue Year 2025 Volume: 9 Issue: 2

Cite

APA Koruk, T., & Bilgin, T. T. (2025). Unveiling trends: a comprehensive analysis of state funded projects of Türkiye through content analysis and text mining. Turkish Journal of Engineering, 9(2), 237-249. https://doi.org/10.31127/tuje.1538068
AMA Koruk T, Bilgin TT. Unveiling trends: a comprehensive analysis of state funded projects of Türkiye through content analysis and text mining. TUJE. January 2025;9(2):237-249. doi:10.31127/tuje.1538068
Chicago Koruk, Talha, and Turgay Tugay Bilgin. “Unveiling Trends: A Comprehensive Analysis of State Funded Projects of Türkiye through Content Analysis and Text Mining”. Turkish Journal of Engineering 9, no. 2 (January 2025): 237-49. https://doi.org/10.31127/tuje.1538068.
EndNote Koruk T, Bilgin TT (January 1, 2025) Unveiling trends: a comprehensive analysis of state funded projects of Türkiye through content analysis and text mining. Turkish Journal of Engineering 9 2 237–249.
IEEE T. Koruk and T. T. Bilgin, “Unveiling trends: a comprehensive analysis of state funded projects of Türkiye through content analysis and text mining”, TUJE, vol. 9, no. 2, pp. 237–249, 2025, doi: 10.31127/tuje.1538068.
ISNAD Koruk, Talha - Bilgin, Turgay Tugay. “Unveiling Trends: A Comprehensive Analysis of State Funded Projects of Türkiye through Content Analysis and Text Mining”. Turkish Journal of Engineering 9/2 (January 2025), 237-249. https://doi.org/10.31127/tuje.1538068.
JAMA Koruk T, Bilgin TT. Unveiling trends: a comprehensive analysis of state funded projects of Türkiye through content analysis and text mining. TUJE. 2025;9:237–249.
MLA Koruk, Talha and Turgay Tugay Bilgin. “Unveiling Trends: A Comprehensive Analysis of State Funded Projects of Türkiye through Content Analysis and Text Mining”. Turkish Journal of Engineering, vol. 9, no. 2, 2025, pp. 237-49, doi:10.31127/tuje.1538068.
Vancouver Koruk T, Bilgin TT. Unveiling trends: a comprehensive analysis of state funded projects of Türkiye through content analysis and text mining. TUJE. 2025;9(2):237-49.
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