| 1 | Abel, F. et al. Analyzing the blogosphere for predicting the success of music and movie products. In ASONAM. Odense, Denmark, pp. 276–280, 2010. |  | 
																		
							| 2 | Agrawal, R. et al. Fast algorithms for mining association rules. In VLDB. Vol. 1215. pp. 487–499, 1994. |  | 
																		
							| 3 | Calefato, F. et al. Collaboration success factors in an online music community. In ACM GROUP. Sanibel Island, USA, 2018. |  | 
																		
							| 4 | Cosimato, A. et al. The conundrum of success in music: Playing it or talking about it? IEEE Access vol. 7, pp. 123289–123298, 2019. |  | 
																		
							| 5 | Dhanaraj, R. and Logan, B. Automatic prediction of hit songs. In ISMIR. pp. 488–491, 2005. |  | 
																		
							| 6 | Fontes, S. G. et al. Association rules mining applied in the animal movement exploratory analysis. In KDMiLe. SBC, pp. 1–8, 2019. |  | 
																		
							| 7 | Gienapp, L. et al. Topological properties of music collaboration networks: The case of jazz and hip hop. Digit. Humanit. Q. 15 (1), 2021. |  | 
																		
							| 8 | Iloga, S. et al. A sequential pattern mining approach to design taxonomies for hierarchical music genre recognition. Pattern Anal. Appl. 21 (2): 363–380, 2018. |  | 
																		
							| 9 | Mayerl, M. et al. Pairwise learning to rank for hit song prediction. In BTW. LNI, vol. P-331. Gesellschaft für Informatik e.V., pp. 555–565, 2023. |  | 
																		
							| 10 | Melo, E. et al. Combining Data Mining Techniques to Analyse Factors Associated with Allocation of Socioeconomic Resources at IFMG. In KDMiLe. SBC, pp. 89–96, 2021. |  | 
																		
							| 11 | Oliveira, G. P. et al. Detecting collaboration profiles in success-based music genre networks. In ISMIR. pp. 726–732,
2020. |  | 
																		
							| 12 | Ordanini, A. et al. The featuring phenomenon in music: how combining artists of different genres increases a song’s
popularity. Market. Letters vol. 29, pp. 485–499, 2018. |  | 
																		
							| 13 | Ren, J. and Kauffman, R. J. Understanding music track popularity in a social network. In ECIS. AIS, Atlanta,
GA, USA, pp. 374–388, 2017. |  | 
																		
							| 14 | Rompré, L. et al. Using association rules mining for retrieving genre-specific music files. In FLAIRS Conference.
AAAI Press, pp. 706–711, 2017. |  | 
																		
							| 15 | Shin, S. and Park, J. On-chart success dynamics of popular songs. Adv. in Comp. Systems 21 (3-4): 1850008, 2018. |  | 
																		
							| 16 | Silva, M. O. et al. Collaboration as a driving factor for hit song classification. In WebMedia. ACM, pp. 66–74, 2022. |  | 
																		
							| 17 | Zaki, M. J. and Meira Jr., W. Data Mining and Analysis: Fundamental Concepts and Algorithms. Cambridge
University Press, 2014. |  | 
																		
							| 18 | Zangerle, E. et al. Hit song prediction: Leveraging low- and high-level audio features. In ISMIR. pp. 319–326, 2019. |  |