摘要
[目的/意义]为大数据环境下针对舆情的发生和演化提出适当应对方式和手段提供参考。[方法/过程]基于调和K均值聚类分析原理,提出一种用于判断舆情演化趋势的预测预警模型,并将粒子群优化嵌入模型以加速大数据环境下的算法收敛,提升算法的时间性。[结果/结论]通过仿真实验验证了该模型的有效性,对网络舆情预测与研判具有一定的可行性和实用性。
[Purpose/significance]The paper is to provide reference for putting forwards appropriate coping ways in view of occurrence and evolution of public opinion in the environment of big data. [Method/process]The paper bases theory of k-harmonic means clustering analysis, presents a prediction and early warning model to judge evolution trend of public opinion, and embeds particle swarm optimization into the model to speed up convergence in the environment of big data to improve time performance of the algorithm. [Result/conclusion]The paper verifies the validity of the proposed model by simulation experiment, and the model has certain feasibility and practicability in Internet public opinion prediction.
出处
《情报探索》
2017年第5期6-9,共4页
Information Research
基金
教育部人文社会科学研究青年基金项目"大数据环境下网络舆情热点事件趋势分析及预测模型研究"(项目编号:14YJCZH110)成果之一
关键词
网络舆情
调和K均值
粒子群优化
舆情分析与预警
Internet public opinion
k-harmonic means
particle swarm optimization
public opinion analysis and early warning
