基于文本挖掘的微信公众号文本内容传播特征研究——以“北京农业”微信公众号为例  

Research on the Dissemination Characteristics of the Text Content of WeChat Official Accounts Based on Text Mining—Taking the WeChat Public Account of “Beijing Agriculture” as an Example

作　　者：吕金宝 

机构地区：[1]北京市农业农村宣传中心,北京

出　　处：《数据挖掘》2023年第4期279-287,共9页Hans Journal of Data Mining

摘　　要：目的/意义:从北京农业微信公众号推送文章出发,爬取文本内容,对微信推送文章的外部特征及传播特征进行了分析,以期能从微信公众号推文内容角度为农业知识传播提供参考与借鉴。方法/过程:利用Python语言编写爬虫代码及各种计算脚本,将获取的5103条推文作为数据样本,结合主题词抽取、文本聚类、以及高频词共现网络,分析了北京农业微信公众号推文现状及内容传播特征。结果/结论:北京农业微信公众号在农业知识传播的内容组织方面已较为全面,在深刻剖析传播特征的基础上,应着力从需求挖掘、创造热点等方面让推文更有热度。Purpose/Meaning: Starting from the crawled Beijing Agricultural WeChat official account push articles, the external characteristics and dissemination characteristics of WeChat articles are analyzed, in order to provide reference for the dissemination of agricultural knowledge from the perspective of the content of the WeChat official account tweets. Method/Process: Using Python language to write crawler system and various calculation scripts, 5103 tweets obtained as data samples, combined with text clustering, LDA topic model and high-frequency word co-occurrence network, analyzed the public of Beijing Agricultural WeChat Status of Tweet No. and the characteristics of con-tent dissemination. Results/Conclusions: The Beijing Agricultural WeChat official account should be more comprehensive in the content organization of agricultural knowledge dissemination. Based on the in-depth analysis of the characteristics of dissemination, efforts should be made to make tweets more popular in terms of demand mining and creation of hot spots.

关 键 词：PYTHON语言 文本挖掘 微信公众号 文本聚类 词共现网络 爬虫 脚本 外部特征 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]