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基于社会网络分析的数据挖掘方法研究

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随着互联网技术的飞速发展,互联网的访问量逐渐增大,由此形成了大规模的虚拟社交网络数据.巨量的网络数据中有效和无效的数据互相掺杂,在分析当前社交舆情时如何从中挖掘有效且有价值的数据和信息成为重点研究问题.运用社会网络分析的数据挖掘方法,探讨了社会网络分析方法在研究社交网络信息关联性和舆情分析上的可行性,并立足于当前实际,选择使用Python抓取网页信息,并利用权威网页和神经网络方法对社会网络数据进行分析预测.
Research on Data Mining Methods Based on Social Network Analysis
With the rapid development of Internet technology and the increasing volume of Internet traf-fic,a large amount of virtual social network data has been generated.In the vast amount of network da-ta,effective and ineffective data are mixed together.How to mine effective and valuable data and informa-tion from it when analyzing current social public opinion has become a key research issue.This paper dis-cusses the feasibility of social network analysis methods in studying the correlation of social network infor-mation and public opinion analysis,and based on the current reality,it selects Python to scrape web-page information,and uses authoritative webpages and neural network methods to analyze and predict so-cial network data.

virtual network social datasocial network analysisdata miningneural networks

赵倩

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安徽警官职业学院,安徽 合肥 230001

虚拟网络社交数据 社会网络分析 数据挖掘 神经网络

2024

安徽警官职业学院学报
安徽警官职业学院

安徽警官职业学院学报

影响因子:0.139
ISSN:1671-5101
年,卷(期):2024.23(5)