Monetising user generated content using data mining techniques

Social media systems such as YouTube are gaining phenomenal popularity. As they face increasing pres-sure and dificulties monetising the large amount of user-generated content, there are intense interests in technologies capable of delivering revenue to the own-ers. In this paper, we propose to use data min-ing techniques to help companies increase their rev-enue stream. Our approach differs principally in the underlying monetisation model and hence, the algo-rithms and data utilised. Our new model assumes both consumer and commercial content being entirely user-generated. We first present an algorithm to demonstrate one of possible monetisation technique that could be used in social media systems such as YouTube. A large volume of real-data harvested from YouTube will also be discussed and made available for the community to potentially kick start research in this direction. © 2009, Australian Computer Society, Inc.