Sunday, 20 December 2009
The boffins at Hewlett Packard's Social Computing Lab reckon they I have come up with a way to predict how 'viral' or popular a piece on content, such as a YouTube vid, would be. The blog post here explains it very well. In summary, they looked at 7000 YouTube videos and 60 million stories on Digg to work out what becomes popular and what doesn't, as part of the testing of a new product called iCatcher.
I'm sure the new software will be snapped up by Ad-land to help predict ad revenue. However, it could also be invaluable in the world of earned media to plan and predict the outcomes of social media campaigns.