Efficiently supporting ad hoc queries in large datasets of time sequences
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Graph evolution: Densification and shrinking diameters
ACM Transactions on Knowledge Discovery from Data (TKDD)
Contents-Based Analysis of Community Formation and Evolution in Blogspace
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Extraction of a latent blog community based on subject
Proceedings of the 18th ACM conference on Information and knowledge management
An analysis of information diffusion in the blog world
Proceedings of the 1st ACM international workshop on Complex networks meet information & knowledge management
Tensor Decompositions and Applications
SIAM Review
The information diffusion model in the blog world
Proceedings of the 3rd Workshop on Social Network Mining and Analysis
Determining content power users in a blog network
Proceedings of the 3rd Workshop on Social Network Mining and Analysis
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A blogosphere is a representative example of online social networks. In this paper, we address spectral analysis of a blogosphere. We model a real-world blogosphere as a matrix and a tensor, and then analyze it by using the SVD and PARAFAC decomposition. According to the results, the SVD successfully identified communities, each of which focuses on a specific topic, and also found hub blogs and authoritative posts within each community. The PARAFAC decomposition also succeeded in extracting more communities of finer granules than the SVD. Also, the PARAFAC decomposition could identify the dominant keywords in addition to the hub blogs and authoritative posts honored in each community.