摘要
现有研究忽略网络舆情演化过程的多成分特性,导致演化分析与建模效果较差。为此,提出一种基于经验模态分解(EMD)的网络舆情演化分析与建模方法。对演化过程进行EMD分解,形成演化过程的趋势成分、周期成分、突发成分和随机成分,通过对各成分进行分析与建模,实现网络舆情的演化分析与建模。实验结果表明,该方法通过EMD分解得到的各成分物理含义明显,有助于分析网络舆情的演化规律,同时具有较好的趋势预测效果,适合进行演化建模。
The existing methods ignore multicomponent characteristics of evolution process of lntemet public opinions, which leads to an unsatisfactory performance of analysis and modeling. To deal with the problem, this paper presents an evolution analysis and modeling method of Interact public opinions based on Empirical Mode Deeomposition（EMD）. It decomposes the evolution process of Internet public opinions by EMD, to form trend component, period component, mutation component and random component. Then it analyzes and models the evolution process of Interact public opinions by analyzing and modeling the above-mentioned components. Experiments show that the components decomposed by EMD have clear physical meanings, which can help to analyze the evolution patterns of Internet public opinions; at the same time, the method has good forecasting performance, thus is more suitable.
出处
《计算机工程》
CAS
CSCD
2012年第21期5-9,共5页
Computer Engineering
基金
国家"863"计划基金资助项目(2007AA01Z439)
国家社会科学基金资助重大项目(09&ZD014)
全军军事学研究生课题基金资助项目
关键词
网络舆情
演化分析
演化建模
趋势预测
经验模态分解
时间序列
Internet public opinions
evolution analysis
evolution modeling
trend forecasting
empirical mode decomposition
time series
