Digging in the Digg Social News Website

The rise of social media aggregating websites provides platforms where users can actively publish, evaluate, and disseminate content in a collaborative way. In this paper, we present a large-scale empirical study about “Digg.com”, one of the biggest social media aggregating websites. Our analysis is based on crawls of 1.5 million users and 10 million published stories on Digg. We study the distinct network structure, the collaborative user characteristics, and the content dissemination process on Digg. We empirically illustrate that friendship relations are used effectively in disseminating half of the content, although there exists a high overlap between the interests of friends. A successful content dissemination process can also be performed by random users who are browsing and digging stories. Since 88% of the published content on Digg is defined as news, it is important for the content to obtain sufficient votes in a short period of time before becoming obsolete. Finally, we show that the synchronization of users´ activities in time is the key to a successful content dissemination process. The dynamics between users´ voting activities consequently decrease the efficiency of friendship relations during content dissemination. The results presented in this paper define basic observations and measurements to understand the underlying mechanism of disseminating content in current online social news aggregators. These findings are helpful to understand the influence of service interfaces and user behaviors on content dissemination.