Predicting Music Success Based on Users' Comments on Online Social Networks - Araújo, Carlos V. S.; M. Neto, Rayol; Nakamura, Fabíola G.; Nakamura, Eduardo F. (Proceedings of the Brazilian Symposium on Multimedia and the Web (WebMedia), 2017)
In this paper, we aim at determining whether or not we can predict the success of a music album, based on the comments posted on social networks during 30 days before the album release. For that matter, we focused on the Twitter network for gathering the user comments. As success measures, we considered the Spotify Popularity and the Billboard Units. The reason for those choices is that Spotify represents the most popular type of music consumption today (audio streaming), while Billboard ranking still favors the old school market (physical albums). As a result, we found out that the amount of Positive Tweets (30 days before the album release) can explain 95.5% of the variation in the Spotify Popularity with a simple linear model. On the other hand, we could not find statistical evidence that the volume of comments on Twitter correlates with the album success measured by the Billboard magazine.