document: Spotting out emerging artists using geo-aware analysis of P2P query strings Record label companies would like to identify potential artists as early as possible in their careers , before other companies approach the artists with competing contracts . The vast number of candidates makes the process of identifying the ones with high success potential time consuming and laborious . This paper demonstrates how datamining of P2P query strings can be used in order to mechanize most of this detection process . Using a unique intercepting system over the Gnutella network , we were able to capture an unprecedented amount of geographically identified ( geo-aware ) queries , allowing us to investigate the diffusion of music related queries in time and space . Our solution is based on the observation that emerging artists , especially rappers , have a discernible stronghold of fans in their hometown area , where they are able to perform and market their music . In a file sharing network , this is reflected as a delta function spatial distribution of content queries . Using this observation , we devised a detection algorithm for emerging artists , that looks for performers with sharp increase in popularity in a small geographic region though still unnoticable nation wide . The algorithm can suggest a short list of artists with breakthrough potential , from which we showed that about 30 % translate the potential to national success .
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