Publication Date

Spring 2012

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

Abstract

This project addresses the problem of identifying influential bloggers in a web blog community. It investigates the problem of identifying influential bloggers by scoring each blog post, posted by bloggers, based on influential factors and ranking bloggers accordingly. There exists preliminary models that attempted to solve the problem but they lack some of important aspects of the blogosphere. In this project we try to combine and improve the methodologies and ideas present in the previous models. We have introduced a new influence factor, which is a combination of facebook likes and shares, into the literature that can further evaluate blog posts efficiently. To capture the true influence we have mined each comment on a blog post to know the tone (agree or disagree) of the commenter, and evaluated the post accordingly. We also utilized the novelty parameter in our approach which represents the quality or goodness of the blog post. The experiment results proved that our approach is able to capture the true influence of each blog post and rank bloggers efficiently.

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