PREDICTIVE ANALYTICS FOR ARTIST CAREER DEVELOPMENT
DOI:
https://doi.org/10.29121/shodhkosh.v6.i1s.2025.6674Keywords:
Predictive Analytics, Artist Career Development, Machine Learning, Talent Management, Data Science, Entertainment IndustryAbstract [English]
The use of data analytics and artificial intelligence in tandem has led to changes in the talent management processes in the entertainment industry. By looking at measured signs of success, predictive analytics provides us with a data-driven method of understanding and predicting how an artist's work will go. This research suggests a complete way to guess how an artist's career will develop using many different types of data, such as action on social media, live numbers, patterns of cooperation and how involved the audience is. The study is based on entertainment data models that already exist and expands them by using advanced machine learning techniques. The method comprises gathering information in a pre-planned manner from a large number of people who practice their religion on public and digital platforms, including the number of followers, engagement metrics, streaming statistics, and genre preferences. These characteristics are inputted into prediction models such as regression analysis, decision trees, and ensemble learning algorithms. These models attempt to identify the factors that are most influential on an artist's development. Strong preparation, feature engineering and cross-validation methods are emphasised in the suggested framework to make sure model stability and reduce overfitting. A case study is carried out on a few artists of different styles to evaluate the applicability of the model to real life. Revisiting historical data provides us with a way to determine how well we are doing at predicting, and it also gives us insights into the management of artists and planning for the future.
References
Al Darayseh, A. (2023). Acceptance of Artificial Intelligence in Teaching Science: Science Teachers’ Perspective. Computers and Education: Artificial Intelligence, 4, Article 100132. https://doi.org/10.1016/j.caeai.2023.100132 DOI: https://doi.org/10.1016/j.caeai.2023.100132
Balcombe, L. (2023). AI Chatbots in Digital Mental Health. Informatics, 10, Article 82. https://doi.org/10.3390/informatics10040082 DOI: https://doi.org/10.3390/informatics10040082
Chen, X., and Ibrahim, Z. (2023). A Comprehensive Study of Emotional Responses in AI-Enhanced Interactive Installation art. Sustainability, 15, Article 15830. https://doi.org/10.3390/su152215830 DOI: https://doi.org/10.3390/su152215830
Cheng, M. (2022). The Creativity of Artificial Intelligence in Art. Proceedings, 81, Article 110. https://doi.org/10.3390/proceedings2022081110 DOI: https://doi.org/10.3390/proceedings2022081110
de Winter, J. C. F., Dodou, D., and Stienen, A. H. A. (2023). ChatGPT in Education: Empowering Educators Through Methods for Recognition and Assessment. Informatics, 10, Article 87. https://doi.org/10.3390/informatics10040087 DOI: https://doi.org/10.3390/informatics10040087
Guo, D. H., Chen, H. X., Wu, R. L., and Wang, Y. G. (2023). AIGC Challenges and Opportunities Related to Public Safety: A Case Study of ChatGPT. Journal of Safety Science and Resilience, 4, 329–339. https://doi.org/10.1016/j.jnlssr.2023.08.001 DOI: https://doi.org/10.1016/j.jnlssr.2023.08.001
Hamal, O., el Faddouli, N. E., Alaoui Harouni, M. H., and Lu, J. (2022). Artificial Intelligent in Education. Sustainability, 14, Article 2862. https://doi.org/10.3390/su14052862 DOI: https://doi.org/10.3390/su14052862
Holmes, W. (2024). AIED—Coming of age? International Journal of Artificial Intelligence in Education, 34, 1–11. https://doi.org/10.1007/s40593-023-00352-3 DOI: https://doi.org/10.1007/s40593-023-00352-3
Ivanova, M., Grosseck, G., and Holotescu, C. (2024). Unveiling Insights: A Bibliometric Analysis of Artificial Intelligence in Teaching. Informatics, 11, Article 10. https://doi.org/10.3390/informatics11010010 DOI: https://doi.org/10.3390/informatics11010010
Kulkarni, P. P., Bhagat, S., Kushwaha, M., Kolase, S., and Korabu, N. (2025). Alfred X Wayne Assistant: A Next-Gen, AI-Powered Digital Assistant. International Journal of Research in Applied Engineering and Technology (IJRAET), 14(2), 53–56.
Leong, W. Y., and Zhang, J. B. (2025). AI on Academic Integrity and Plagiarism Detection. ASM Science Journal, 20(1), Article 75. https://doi.org/10.32802/asmscj.2025.1918 DOI: https://doi.org/10.32802/asmscj.2025.1918
Leong, W. Y., and Zhang, J. B. (2025). Ethical Design of AI for Education and Learning Systems. ASM Science Journal, 20, 1–9. https://doi.org/10.32802/asmscj.2025.1917 DOI: https://doi.org/10.32802/asmscj.2025.1917
Ning, Y., Zhang, C., Xu, B., Zhou, Y., and Wijaya, T. T. (2024). Teachers’ AI-TPACK: Exploring the Relationship Between Knowledge Elements. Sustainability, 16, Article 978. https://doi.org/10.3390/su16030978 DOI: https://doi.org/10.3390/su16030978
Rodrigues, O. S., and Rodrigues, K. S. (2023). A Inteligência Artificial na Educação: Os Desafios do ChatGPT. Texto Livre, 16, e45997. https://doi.org/10.1590/1983-3652.2023.45997 DOI: https://doi.org/10.1590/1983-3652.2023.45997
Shao, L. J., Chen, B. S., Zhang, Z. Q., Zhang, Z., and Chen, X. R. (2024). Artificial Intelligence Generated Content (AIGC) in Medicine: A Narrative Review. Mathematical Biosciences and Engineering, 21(1), 1672–1711. https://doi.org/10.3934/mbe.2024073 DOI: https://doi.org/10.3934/mbe.2024073
Wang, Y., and Yang, S. (2024). Constructing and Testing AI International Legal Education Coupling-Enabling Model. Sustainability, 16, Article 1524. https://doi.org/10.3390/su16041524 DOI: https://doi.org/10.3390/su16041524
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Dr. Hemalatha BS, Dr. Sucheta Kanchi, Rashmi Manhas, Vivek Saraswat, Lovish Dhingra, Deepthi S
This work is licensed under a Creative Commons Attribution 4.0 International License.
With the licence CC-BY, authors retain the copyright, allowing anyone to download, reuse, re-print, modify, distribute, and/or copy their contribution. The work must be properly attributed to its author.
It is not necessary to ask for further permission from the author or journal board.
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
