Community structures and role detection in music networks
We analyze the existence of community structures in two different social networks using data obtained from similarity and collaborative features between musical artists. Our analysis reveals some characteristic organizational patterns and provides information about the driving forces behind the grow...
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2008
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_10541500_v18_n4_p_Teitelbaum http://hdl.handle.net/20.500.12110/paper_10541500_v18_n4_p_Teitelbaum |
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paper:paper_10541500_v18_n4_p_Teitelbaum2023-06-08T16:03:05Z Community structures and role detection in music networks Teitelbaum, Tomás Balenzuela, Pablo algorithm automated pattern recognition biological model computer simulation cooperation interpersonal communication music procedures social support Algorithms Communication Computer Simulation Cooperative Behavior Models, Biological Music Pattern Recognition, Automated Social Support We analyze the existence of community structures in two different social networks using data obtained from similarity and collaborative features between musical artists. Our analysis reveals some characteristic organizational patterns and provides information about the driving forces behind the growth of the networks. In the similarity network, we find a strong correlation between clusters of artists and musical genres. On the other hand, the collaboration network shows two different kinds of communities: rather small structures related to music bands and geographic zones, and much bigger communities built upon collaborative clusters with a high number of participants related through the period the artists were active. Finally, we detect the leading artists inside their corresponding communities and analyze their roles in the network by looking at a few topological properties of the nodes. © 2008 American Institute of Physics. Fil:Teitelbaum, T. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Balenzuela, P. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2008 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_10541500_v18_n4_p_Teitelbaum http://hdl.handle.net/20.500.12110/paper_10541500_v18_n4_p_Teitelbaum |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
algorithm automated pattern recognition biological model computer simulation cooperation interpersonal communication music procedures social support Algorithms Communication Computer Simulation Cooperative Behavior Models, Biological Music Pattern Recognition, Automated Social Support |
| spellingShingle |
algorithm automated pattern recognition biological model computer simulation cooperation interpersonal communication music procedures social support Algorithms Communication Computer Simulation Cooperative Behavior Models, Biological Music Pattern Recognition, Automated Social Support Teitelbaum, Tomás Balenzuela, Pablo Community structures and role detection in music networks |
| topic_facet |
algorithm automated pattern recognition biological model computer simulation cooperation interpersonal communication music procedures social support Algorithms Communication Computer Simulation Cooperative Behavior Models, Biological Music Pattern Recognition, Automated Social Support |
| description |
We analyze the existence of community structures in two different social networks using data obtained from similarity and collaborative features between musical artists. Our analysis reveals some characteristic organizational patterns and provides information about the driving forces behind the growth of the networks. In the similarity network, we find a strong correlation between clusters of artists and musical genres. On the other hand, the collaboration network shows two different kinds of communities: rather small structures related to music bands and geographic zones, and much bigger communities built upon collaborative clusters with a high number of participants related through the period the artists were active. Finally, we detect the leading artists inside their corresponding communities and analyze their roles in the network by looking at a few topological properties of the nodes. © 2008 American Institute of Physics. |
| author |
Teitelbaum, Tomás Balenzuela, Pablo |
| author_facet |
Teitelbaum, Tomás Balenzuela, Pablo |
| author_sort |
Teitelbaum, Tomás |
| title |
Community structures and role detection in music networks |
| title_short |
Community structures and role detection in music networks |
| title_full |
Community structures and role detection in music networks |
| title_fullStr |
Community structures and role detection in music networks |
| title_full_unstemmed |
Community structures and role detection in music networks |
| title_sort |
community structures and role detection in music networks |
| publishDate |
2008 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_10541500_v18_n4_p_Teitelbaum http://hdl.handle.net/20.500.12110/paper_10541500_v18_n4_p_Teitelbaum |
| work_keys_str_mv |
AT teitelbaumtomas communitystructuresandroledetectioninmusicnetworks AT balenzuelapablo communitystructuresandroledetectioninmusicnetworks |
| _version_ |
1768546549641510912 |