  Blogs-Online digital diary like application on web 2.0 has opened new and
easy way to voice opinion, thoughts, and like-dislike of every Internet user to
the World. Blogosphere has no doubt the largest user-generated content
repository full of knowledge. The potential of this knowledge is still to be
explored. Knowledge discovery from this new genre is quite difficult and
challenging as it is totally different from other popular genre of
web-applications like World Wide Web (WWW). Blog-posts unlike web documents are
small in size, thus lack in context and contain relaxed grammatical structures.
Hence, standard text similarity measure fails to provide good results. In this
paper, specialized requirements for comparing a pair of blog-posts is
thoroughly investigated. Based on this we proposed a novel algorithm for
sentence oriented semantic similarity measure of a pair of blog-posts. We
applied this algorithm on a subset of political blogosphere of Pakistan, to
cluster the blogs on different issues of political realm and to identify the
influential bloggers.
