Modern Information Retrieval
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Small Worlds: The Dynamics of Networks between Order and Randomness
Small Worlds: The Dynamics of Networks between Order and Randomness
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Statistical properties of community structure in large social and information networks
Proceedings of the 17th international conference on World Wide Web
Learning query intent from regularized click graphs
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
An analysis of information diffusion in the blog world
Proceedings of the 1st ACM international workshop on Complex networks meet information & knowledge management
| Hi-index | 0.00 |
The blog world is a representative online society. To understand the nature of the blog world, there have been many research efforts on analyzing information diffusion and blog-ger activities. The independent cascade model is appropriate to explain information diffusion in the blog world. For the model to be employed, the blog world should be represented as a form of a network. For accurate analysis, it is crucial to assign a diffusion probability to each edge between a pair of bloggers in the blog network. In this paper, we propose a novel method to assign a diffusion probability to an edge for a pair of bloggers that reflects well the phenomenon of actual information diffusion between them. We verify the superiority of our approach by performing extensive experiments with real-world blog data.