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

Year 2026, Volume: 9 Issue: 2, 646 - 663, 15.03.2026

Hunaıda Avvad

https://doi.org/10.34248/bsengineering.1772673

https://izlik.org/JA78ZH54PS

Abstract

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.

Keywords

Machine learning , Crowdfunding , Prediction , Classification

Ethical Statement

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.

References

• Akyildiz, B., Metin-Camgöz, S., & Atici, K. B. (2021). Kitlesel fonlama projelerinin başarılarını etkileyen faktörler üzerine bir inceleme. Sosyoekonomi, 29(50), 521–545.
• 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.
• 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.
• 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.
• 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.
• Altunkaya, S. M., & Özcan, M. (2021). Yenilenebilir enerji yatırımlarının finansmanında kullanılabilecek yeni nesil finansman mekanizmaları. Applied Ecology and Environmental Research, 21(5), 35–43.
• 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.
• 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.
• Boye, D., Ozcan, S., & Fajana, O. (2023). Text mining approach for identifying product ideas and trends based on crowdfunding projects. IEEE Transactions on Engineering Management, 71, 7112–7127.
• Bulut, E. (2022). Blockchain-based entrepreneurial finance: Success determinants of tourism initial coin offerings. Current Issues in Tourism, 25(11), 1767–1781.
• Chen, Y. J., Dai, T., Korpeoglu, C. G., Sahin, O., Tang, C. S., & Xiao, S. (2018). Innovative online platforms: Research opportunities. SSRN Electronic Journal, 1–31.
• Çubukcu, A., Ulusoy, T., & Boz, E. Y. (2020). Crowdfunding and open innovation together: A conceptual framework of a hybrid crowd innovation model. International Journal of Innovation and Technology Management, 17(08), 2150003.
• Demir, T., Mohammadi, A., & Shafi, K. (2022). Crowdfunding as gambling: Evidence from repeated natural experiments. Journal of Corporate Finance, 77, 101905.
• Demiray, M., Burnaz, S., & Li, D. (2021). Effects of institutions on entrepreneurs’ trust and engagement in crowdfunding. Journal of Electronic Commerce Research, 22(2), 95–109.
• Demirdöğen, Y. (2021). New resources for Islamic finance: Islamic fintech. Hitit Theology Journal, 20(3), 29–56.
• Ekici, O., & Aytürk, Y. (2023). The role of consumer confidence and inflation in crowdfunding success. International Journal of Entrepreneurial Venturing, 15(4), 295–316.
• Elitzur, R., Katz, N., Muttath, P., & Soberman, D. (2024). The power of machine learning methods to predict crowdfunding success: Accounting for complex relationships efficiently. Journal of Business Venturing Design, 3, 100022.
• Gunduz, H. (2024). Comparative analysis of BERT and FastText representations on crowdfunding campaign success prediction. PeerJ Computer Science, 10, e2316.
• Kilinc, M., & Aydin, C. (2023). Feature selection for Turkish crowdfunding projects using filtering and wrapping methods. Electronic Commerce Research and Applications, 62, 101340.
• Kilinc, M., Aydin, C., & Tarhan, C. (2022). CFTest: Web-based business intelligence application that measures crowdfunding success. Proceedings of the International Conference on Innovations in Intelligent Systems and Applications (ASYU), 1–5.
• Koçer, S. (2015). Social business in online financing: Crowdfunding narratives of independent documentary producers in Türkiye. New Media & Society, 17(2), 231–248.
• Marina, A., Wahjono, S. I., Fam, S. F., & Rasulong, I. (2023). Crowdfunding to finance SMEs: New model after pandemic disease. Sustainable Science Resources, 5, 1–19.
• Meng, Y., Wu, H., Zhao, W., Chen, W., Dinçer, H., & Yüksel, S. (2021). A hybrid heterogeneous Pythagorean fuzzy group decision modelling for crowdfunding development process pathways of fintech-based clean energy investment projects. Financial Innovation, 7(1), 61.
• Mollick, E. (2014). The dynamics of crowdfunding: An exploratory study. Journal of Business Venturing, 29(1), 1–16.
• Napari, A., Ozcan, R., & Khan, A. U. I. (2023). The language of sustainability: Exploring the implications of metaphors on environmental action and finance. Applied Ecology and Environmental Research, 21(5), 4653–4675.
• Oduro, M. S., Yu, H., & Huang, H. (2022). Predicting the entrepreneurial success of crowdfunding campaigns using model-based machine learning methods. International Journal of Crowd Science, 6(1), 7–16.
• Ozcan, S., Boye, D., Arsenyan, J., & Trott, P. (2022). A scientometric exploration of crowdsourcing: Research clusters and applications. IEEE Transactions on Engineering Management, 69(6), 3023–3037.
• Özdemir, M., & Selçuk, M. (2021). A bibliometric analysis of the International Journal of Islamic and Middle Eastern Finance and Management. International Journal of Islamic and Middle Eastern Finance and Management, 14(4), 767–791.
• Özdemir, V., Faris, J., & Srivastava, S. (2015). Crowdfunding 2.0: The next-generation philanthropy. EMBO Reports, 16(3), 267–271.
• Saiti, B., Afghan, M., & Noordin, N. H. (2018a). Financing agricultural activities in Afghanistan: A proposed salam-based crowdfunding structure. ISRA International Journal of Islamic Finance, 10(1), 52–61.
• Saiti, B., Musito, M. H., & Yucel, E. (2018b). Islamic crowdfunding: Fundamentals, developments and challenges. The Islamic Quarterly, 62(3), 469–485.
• Seidl, A., Cumming, T., Arlaud, M., Crossett, C., & van den Heuvel, O. (2024). Investing in the wealth of nature through biodiversity and ecosystem service finance solutions. Ecosystem Services, 66, 101601.
• Seidl, A., Wallace, K., Cruz-Trinidad, A., Ogena, A., Nirannoot, N., Plantilla, A., Mora, A., Martinez, H. S. L., Salazar, S., Orozco, A. L., & van den Heuvel, O. (2023). Crowdfunding marine and coastal protected areas: Reducing the revenue gap and financial vulnerabilities revealed by COVID-19. Ocean & Coastal Management, 242, 106726.
• Sirma, İ., Ekici, O., & Aytürk, Y. (2019). Crowdfunding awareness in Türkiye. Procedia Computer Science, 158, 490–497.
• Son-Turan, S. (2016). Reforming higher education finance in Türkiye: The alumni-crowdfunded student debt fund “a-CSDF” model. Egitim ve Bilim, 41(184), 267–289.
• Tanrisever, F., & Wismans-Voorbraak, K. A. (2016). Crowdfunding for financing wearable technologies. Proceedings of the Hawaii International Conference on System Sciences (HICSS), 1800–1807.
• Wan, X., Teng, Z., Li, Q., & Deveci, M. (2023). Blockchain technology empowers the crowdfunding decision-making of marine ranching. Expert Systems with Applications, 221, 119685.
• Wu, X., Dinçer, H., & Yüksel, S. (2022). Analysis of crowdfunding platforms for microgrid project investors via a q-rung orthopair fuzzy hybrid decision-making approach. Financial Innovation, 8(1), 46.
• Yasar, B., Yılmaz, I. S., Hatipoğlu, N., & Salih, A. (2022). Stretching the success in reward-based crowdfunding. Journal of Business Research, 152, 205–220.
• Yeh, J. Y., & Chen, C. H. (2022). A machine learning approach to predict the success of crowdfunding fintech project. Journal of Enterprise Information Management, 35(6), 1678–1696.
• Yousaf, Z., Shakaki, O., Isac, N., Cretu, A., & Hrebenciuc, A. (2022). Towards crowdfunding performance through crowdfunding digital platforms: Investigation of social capital and innovation performance in emerging economies. Sustainability, 14(15), 9495.