| 综合时间序列分析和新颖性的信息扩散预测 |
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| 引用本文： | 蔡飞,陈洪辉,舒振. 综合时间序列分析和新颖性的信息扩散预测[J]. 北京邮电大学学报, 2013, 36(1): 59-62 |
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| 作者姓名： | 蔡飞 陈洪辉 舒振 |
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| 作者单位： | 信息系统与管理学院 信息系统工程重点实验室, 长沙 410073 |
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| 基金项目： | 国家自然科学基金项目(61070216) |
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| 摘 要： | 现有信息扩散预测普遍依赖于社会网络构建,从而引发网络链路估计准确率低,信息扩散预测精度差的问题,为此提出了一种综合时间序列分析和信息新颖性的信息扩散预测方法.通过分析信息在网络节点上扩散随时间的变化特性,对网络节点的全局影响力进行估计,并考虑信息产生至节点受影响的时间差来衡量信息新颖性,进而平移调整节点影响力大小,最终实现信息扩散范围的预测.向斯坦福大学所提供测试数据的实验结果表明,新方法准确稳定地预测了信息扩散范围的实时变化.
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| 关 键 词： | 信息扩散预测 时间序列分析 信息新颖性 影响传播 |
| 收稿时间： | 2012-04-22 |
Information Diffusion Prediction Based on Time-Series Analysis and Information Novelty |
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| CAI Fei,CHEN Hong-hui,SHU Zhen. Information Diffusion Prediction Based on Time-Series Analysis and Information Novelty[J]. Journal of Beijing University of Posts and Telecommunications, 2013, 36(1): 59-62 |
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| Authors: | CAI Fei CHEN Hong-hui SHU Zhen |
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| Affiliation: | Science and Technology on Information Systems Engineering Laboratory, College of Information System and Management, Changsha 410073, China |
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| Abstract: | To solve the problem of low precision on information propagation prediction caused by frustrated link prediction in social networks, a new approach, based on time-series analysis, combined with information novelty, is proposed with no requiring the knowledge of social network.When the node is infected, the global influence function of a node is estimated. The overall propagation volume of information is predicted. Simulations on dataset about news articles and blogs show that the proposal can accurately and reliably predict the temporal variations of information diffusion. |
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| Keywords: | information diffusion prediction time-series analysis information novelty influence propagation |
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