Araştırma Makalesi

Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns

Cilt: 9 Sayı: 2 15 Mart 2026
PDF İndir
EN TR

Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns

Öz

As crowdfunding is widely used in finance, researchers have been interested in developing predictive models that can accurately assess crowdfunding campaign success. The purpose of this study is to create a machine learning based decision support system for the determination of crowdfunding campaign success in Türkiye. The study used 24 different machine learning models, and a dataset of 1,628 campaigns collected from 2011 to 2021 with 38 parameters. Tree-based ensemble models (Gradient Boosting, AdaBoost, CatBoost) achieved the highest classification accuracy of 99.4%, and performed much better than traditional classifiers, thereby showing their appropriateness for prediction analytics on crowdfunding success prediction. Accuracy, precision, recall, F1 score, and confidence intervals were used as performance metrics. The proposed framework reveals which features create the most impact on crowdfunding success prediction and finds strong correlations among social media and funding-related features in the crowdfunding dataset, highlighting key predictors like support rate and collected amount while identifying redundant variables to enhance model efficiency.

Anahtar Kelimeler

Etik Beyan

This study was conducted solely through the Scilio platform and did not involve direct intervention with humans or animals. Therefore, approval from an ethics committee was not required.

Kaynakça

  1. Akyildiz, B., Metin-Camgöz, S., & Atici, K. B. (2021). Kitlesel fonlama projelerinin başarılarını etkileyen faktörler üzerine bir inceleme. Sosyoekonomi, 29(50), 521–545.
  2. Alimoglu, A., & Ozturan, C. (2017). Design of a smart contract based autonomous organization for sustainable software. Proceedings of the IEEE International Conference on eScience, 13, 471–476.
  3. Al-Khowarizmi, M., Watts, M. J., Efendi, S., & Kamil, A. A. (2024). Financial technology forecasting using an evolving connectionist system for lenders and borrowers: Ecosystem behavior. IAES International Journal of Artificial Intelligence, 13(2), 2386–2394.
  4. Al-Mulla, A., Ari, I., & Koç, M. (2022). Sustainable financing for entrepreneurs: Case study in designing a crowdfunding platform tailored for Qatar. Digital Business, 2(2), 100032.
  5. Altundal, V. (2024). Can equity-based crowdfunding be a fast and effective financing model for early-stage startups? Journal of the International Council for Small Business, 5(3), 304–329.
  6. Altunkaya, S. M., & Özcan, M. (2021). Yenilenebilir enerji yatırımlarının finansmanında kullanılabilecek yeni nesil finansman mekanizmaları. Applied Ecology and Environmental Research, 21(5), 35–43.
  7. Avci, G., & Erzurumlu, Y. O. (2023). Blockchain tokenization of real estate investment: A security token offering procedure and legal design proposal. Journal of Property Research, 40(2), 188–207.
  8. Aygoren, O., & Koch, S. (2021). Community support or funding amount: Actual contribution of reward-based crowdfunding to market success of video game projects on Kickstarter. Sustainability, 13(16), 9195.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Karar Desteği ve Grup Destek Sistemleri

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

15 Mart 2026

Gönderilme Tarihi

26 Ağustos 2025

Kabul Tarihi

11 Şubat 2026

Yayımlandığı Sayı

Yıl 2026 Cilt: 9 Sayı: 2

Kaynak Göster

APA
Avvad, H. (2026). Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns. Black Sea Journal of Engineering and Science, 9(2), 646-663. https://doi.org/10.34248/bsengineering.1772673
AMA
1.Avvad H. Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns. BSJ Eng. Sci. 2026;9(2):646-663. doi:10.34248/bsengineering.1772673
Chicago
Avvad, Hunaıda. 2026. “Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns”. Black Sea Journal of Engineering and Science 9 (2): 646-63. https://doi.org/10.34248/bsengineering.1772673.
EndNote
Avvad H (01 Mart 2026) Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns. Black Sea Journal of Engineering and Science 9 2 646–663.
IEEE
[1]H. Avvad, “Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns”, BSJ Eng. Sci., c. 9, sy 2, ss. 646–663, Mar. 2026, doi: 10.34248/bsengineering.1772673.
ISNAD
Avvad, Hunaıda. “Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns”. Black Sea Journal of Engineering and Science 9/2 (01 Mart 2026): 646-663. https://doi.org/10.34248/bsengineering.1772673.
JAMA
1.Avvad H. Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns. BSJ Eng. Sci. 2026;9:646–663.
MLA
Avvad, Hunaıda. “Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns”. Black Sea Journal of Engineering and Science, c. 9, sy 2, Mart 2026, ss. 646-63, doi:10.34248/bsengineering.1772673.
Vancouver
1.Hunaıda Avvad. Crowdfunding Success Prediction Using Machine Learning: A Comparative Study Based on Türkiye’s Campaigns. BSJ Eng. Sci. 01 Mart 2026;9(2):646-63. doi:10.34248/bsengineering.1772673

                           24890