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
An Index-Based Approach for Similarity Search Supporting Time Warping in Large Sequence Databases
Proceedings of the 17th International Conference on Data Engineering
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
Exact indexing of dynamic time warping
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Identifying the influential bloggers in a community
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
BlogCast effect on information diffusion in a blogosphere
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Spectral analysis of a blogosphere
Proceedings of the 20th ACM international conference on Information and knowledge management
WAW'12 Proceedings of the 9th international conference on Algorithms and Models for the Web Graph
On the diffusion of messages in on-line social networks
Performance Evaluation
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In the blog network, the posts in a blog can be diffused to other blogs through trackbacks and scraps. Analyzing information diffusion in the blog network is an important research issue that can be used for predicting information diffusion, detecting abnormality, marketing, and revitalizing the blog world. Existing studies on information diffusion in a blog network define explicit relationships between blogs and analyze the word-of-mouth effect through such explicit relationships only. However, it has been observed that more than 85% of all information diffusion in a blog network occurs through non-explicit relationships. In this paper, we propose a new model that considers both the explicit and non-explicit relationships between blogs in order to explain the information diffusion phenomena in a blog network. We add a super node and the relationships between the super node and blogs as broadcast edges and register edges to the existing information diffusion model and assign the assimilation probability to every relationship. The expanded information diffusion model improves the accuracy of the basic model by taking into account the degrees of diffusion powers of posts. We verify the superiority of the proposed model through extensive experiments of information diffusion at a real blog network. The experimental results show that our expanded information diffusion model generates 77% less errors than the existing model.