| Abstract | The phenomenal growth in both scale and importance of so-cial media such as blogs, micro-blogs and user-generated
content, has created a need for tools that monitor information
diffusion and make recommendations within these platforms.
An essential element of social media, particularly blogs, is
the hyperlink graph that connects various pieces of content.
There are two types of links within the blogosphere; one
from blog post to blog post, and another from blog post to
blog channel (an event stream of blog posts). These links
can be viewed as a proxy for the flow of information between
blog channels and to reflect influence. Given this assumption
about links, the ability to predict future links can facilitate
the monitoring of information diffusion, making recommen-
dations, and word-of-mouth (WOM) marketing. We propose
different methods for link predictions and we evaluate these
methods on an extensive blog dataset.
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