Multiple Factors-Aware Diffusion in Social Networks
Abstract
Information diffusion is a natural phenomenon that informationpropagates from nodes to nodes over a social network. The behaviorthat a node adopts an information piece in a social network can beaffected by different factors. Previously, many diffusion models are proposedto consider one or several fixed factors. The factors affecting theadoption decision of a node are different from one to another and maynot be seen before. For a different scenario of diffusion with new factors,previous diffusion models may not model the diffusion well, or are notapplicable at all. In this work, our aim is to design a diffusion modelin which factors considered are flexible to extend and change. We furtherpropose a framework of learning parameters of the model, whichis independent of factors considered. Therefore, with different factors,our diffusion model can be adapted to more scenarios of diffusion withoutrequiring the modification of the diffusion model and the learningframework. In the experiment, we show that our diffusion model is veryeffective on the task of activation prediction on a Twitter dataset.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 22, 2015
- Accession Number
- AD1015839
Entities
People
- Chung-kuang Chou
- Ming-syan Chen
Organizations
- National Taiwan University