With rapid development of web 2.0 technology and e-business, bloggers play significant roles in the whole blogosphere as well as the external world. Specially, the most influential bloggers can bring great business values to modern enterprise in multiple ways, by increasing market profits and enlarging business impacts. The bloggers' influences can be deployed only in a specific domain, e.g. computer companies only can utilize the influence bloggers' expertise in computer knowledge, not their expertise in modern art or others. Despite that several influential bloggers mining systems are available, none of them consider the domain specific feature and their evaluations are based on generic influence, which is not applicable for real application requirements, such as business advertisement, personalized recommendation and so on. In this paper, we propose an effective model to mine the top-k influential bloggers according to their interest domains and network proximity. We investigate an effective algorithm to evaluate a blogger's influence and develop a domain specific influential blogger mining system. The experiment results show that our system can effectively mine influential bloggers and is applicable to diverse applications. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Caiv, Y., & Chen, Y. (2009). Mining influential bloggers: From general to domain specific. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5712 LNAI, pp. 447–454). https://doi.org/10.1007/978-3-642-04592-9_56
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