Identifying influential bloggers using blogs semantics

Web 2.0 has brought a lot of good things for internet audience. Interactive user generated contents like blogs, become a popular means to voice ones opinion related to anything. The blogosphere contains a lot of user's generated contents, a growing readerships and ever increasing thoughts followers. Identifying influential bloggers is a recently introduced phenomenon; influential bloggers have prospects in bringing a great value to business. They can convince their fellow bloggers on variety of grounds, react to the news event and bring a three sixty degree view of the news, create a new thought or perception and can get people under their discernment by their power of thought and content creation. There are many researchers that proposed influential bloggers mining systems, but all these systems suffer from drawbacks like: domain driven, generalized shallow influential measure and validation and verification. We propose in this paper, an effective algorithm to identify influential bloggers by using influence measuring factors. These factors are based on contents semantics of their blog-posts, quantitative analysis of the contents and fellow readerships with their comments on the post. We applied this algorithm, on a subset of political blogosphere of Pakistan, where we have successfully able to indentify influential bloggers; proactive spreads of their influential thinking, and changing views of the fellow readers. We believe that this algorithm can be extended to identify an influential group in groups' blogging.