On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Mining knowledge-sharing sites for viral marketing
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Information flow modeling based on diffusion rate for prediction and ranking
Proceedings of the 16th international conference on World Wide Web
Analyzing a Korean blogosphere: a social network analysis perspective
Proceedings of the 2011 ACM Symposium on Applied Computing
Spectral analysis of a blogosphere
Proceedings of the 20th ACM international conference on Information and knowledge management
Measuring Blog Influence: Recognition, Activity Generation, and Novelty
International Journal of Interactive Communication Systems and Technologies
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In a blog network, there are special users who induce other users to actively utilize blog services. In this paper, these users whose contents exhibit large influence over other users are defined as Content Power Users (CPUs). Accurately determining who content power users are in a blog network is important in order to establish an effective business policy that stimulates usage of blog services. In this paper, we propose a new method of determining content power users. First, we measure the influence of each document owned by individual users. Since the influence of a document tends to be high with long exposure, we adjust the value of influence of a document based on exposure duration. Then, by adding up the values of influence of all the documents owned by each user, we calculate the influence of the corresponding user. We analyze the performance of our method, by applying the proposed method to an actual blog network and comparing its results to those of preexisting methods for determining power users. The experimental results demonstrate that our method is well suited for the dynamic nature of the blog network.