Multivariate analysis of Web content changes

News websites are expected to deliver in a timely manner the latest stories as well as their latest developments. Thereby, tools, such as, search engines, need to cope with these rapid and frequent content changes by adjusting their crawling activities accordingly. In this paper we explore and model the properties and temporal behavior of the content changes of three major news websites. The dynamics of the changes is characterized by large fluctuations and significant differences from day to day and from hour to hour. However, a certain degree of similarity in the overall patterns of each website exists. In particular, the application of multivariate analysis techniques allows us to identify groups of days with similar change patterns, thus allowing for the customization of the crawling policies adopted by search engines.