EconPapers    
Economics at your fingertips  
 

A Gated Recurrent Unit (GRU) Model for Predicting the Popularity of Local Musicians

O. O. Ajayi (), A. O. Olorunda, O. G. Aju () and A. A. Adegbite ()
Additional contact information
O. O. Ajayi: Adekunle Ajasin University
A. O. Olorunda: Adekunle Ajasin University
O. G. Aju: Adekunle Ajasin University
A. A. Adegbite: Adekunle Ajasin University

A chapter in Sustainable Education and Development – Sustainable Industrialization and Innovation, 2023, pp 514-521 from Springer

Abstract: Abstract Purpose: Popular musicians are among the most admired people in the world, and music is one of the features of modern culture that is most universally appreciated. Why one musician is well-liked while others are not is frequently a very tough question to answer. Survey shows most local yet talented musicians were not explored but lost due to unwillingness of music promoters to promote them. This study aims at using Gated Recurrent Unit (GRU) model in predicting the rise and popularity of local musicians by considering some established metrics for the evaluation of local musicians, alongside some characteristics/features. Design/Methodology/Approach: Using the Kaggle dataset of local musicians’ performance characteristics and historical data, the study analyzes certain features of local musicians and predicts their possible future rise, using a GRU Deep Learning Model. Findings: The result shows a high degree (70.1%) of accuracy with a Mean Square Error (MSE) of 0.0069, between the predicted and actual performance. The work shows that the developed model can predict the possible future rise and popularity of local musicians. Research Limitations: Only a few available original data (relating to local unpopular musicians) were extracted and due to time constraints in implementing the work, the authors could not get down to the community to extract more from local musicians around. Practical Implication: The model can be used by music promoters to decide on sealing contract agreements with local/upcoming musicians both for their sustainability and promotability. Originality/Value: While many predictive works were done focusing on music popularity, the song hits rate, and so on, the few that centered their aim on musicians’ popularity only analyzed established musicians. This work however ventures into the analysis of the possible elevation of local musicians by considering certain parameters that relate to their songs.

Keywords: Music; Popularity; Prediction; Promotability; Sustainability (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-25998-2_39

Ordering information: This item can be ordered from
http://www.springer.com/9783031259982

DOI: 10.1007/978-3-031-25998-2_39

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-02
Handle: RePEc:spr:sprchp:978-3-031-25998-2_39