Forecasting Digg.com web traffic

How can time series be predicted, for example to ensure adequate capacity planning? In this example, we analyze traffic logs from popular bookmarking website Digg.com, and build a forecasting model. We also explain how the same technique can be applied to other types of data.

Analyzed data:

The following web traffic variables were made available by website Digg.com:

• Date (day)
• Number of front page articles
• Total number of comments
• Total number of diggs
• Average number of comments per article
• Average number of diggs per article
• Standard deviation of comments per article
• Standard deviation of diggs per article