  Social networks have emerged as a critical factor in information
dissemination, search, marketing, expertise and influence discovery, and
potentially an important tool for mobilizing people. Social media has made
social networks ubiquitous, and also given researchers access to massive
quantities of data for empirical analysis. These data sets offer a rich source
of evidence for studying dynamics of individual and group behavior, the
structure of networks and global patterns of the flow of information on them.
However, in most previous studies, the structure of the underlying networks was
not directly visible but had to be inferred from the flow of information from
one individual to another. As a result, we do not yet understand dynamics of
information spread on networks or how the structure of the network affects it.
We address this gap by analyzing data from two popular social news sites.
Specifically, we extract social networks of active users on Digg and Twitter,
and track how interest in news stories spreads among them. We show that social
networks play a crucial role in the spread of information on these sites, and
that network structure affects dynamics of information flow.
