Recently, one of the main issues of concern within the world wide web is the understanding of web 2.0 mass
collaboration systems. These systems have emerged in recent years and gained enormous popularity. It must, however, be
pointed out, that the potential and practical application of web 2.0 are still not well understood and deserve academic
attention. In this paper we investigate the online media sharing collaborative community and its applications for uses in
stock market analysis and prediction. Specifically, we look at Youtube.com, one of the most popular social media sharing
websites. The association with stock market behaviour and usage patterns are investigated. This work became of more
interest and significance with the recent credit crunch crisis. The data under investigation is novel, and to our knowledge,
this paper reports the first investigation of its kind to the use of collaborative media sharing website for stock market
analysis. We find significant association between video meta-data and textual data using a content driven sentiment text
mining approach. The results are very encouraging and importantly highlight efficient information transfer to online
media sharing communities as there seems to be predictive value in youtube data
