Two great articles on current research into how artists and songs become hits:
Group Think looks at research predicting musical hits using “geo-aware query strings” from file-sharing networks such as Gnutella.
The geographic location of an emerging artist is the key to predicting their success […]. “If an artist has the potential to be successful, people will first start noticing them in the small geographical area where they live and perform.” In fact, a potential pop star will typically enjoy thousands of downloads a day on a local level, while remaining relatively unheard of on a national level. A large divergence between local and global popularity, called the Kullback-Leiber divergence, is a strong indicator of star potential. The algorithm measures the K-L divergence to produce a short list of potentials, of which 15 to 30 percent will go on to reach national popularity within weeks.
Taking a different approach, The Anatomy of a Hit Song shows that what makes many of us like a certain song isn’t its sound; it’s the ‘outside influence’ of our peers liking the song.
While [the researcher] could predict which songs would be popular after an initial round of feedback, he said it’s initially difficult to guess which songs will become popular and which will be despised strictly on their own merits. He cites the performance of the song “Lockdown” by 52metro, which ranked right in the middle among the 48 available tracks by listeners who had no social context. However, in two samples subjected to outside influence, it came in first place in one trial and 40th in the other.
As the article states, these findings aren’t strictly confined to music; the theory likely applies just as much to books, movies and TV shows.