面向微信平台的数据挖掘及行为特征分析

WeChat Platform Oriented Data Mining and Behavior Characteristics Analysis

移动互联网的发展推动微信平台公众号的发展,在微信公众号中,加强数据挖掘与特征分析是其快速推广的关键。基于此,研究利用爬虫等技术构建了微信平台公众号的数据采集模块,并通过实验对其进行了验证。实验结果表明,从某科技大学的官方微信公众号上发布的历史消息来看,该账号在8年内的单日发布次数最高达到了8次;在数据挖掘中,剔除了100001以上的内容后最多阅读量是91217,点赞量是1610,评论数是1027;同时,文章发布最多的是星期二,共544篇,占18.37%。综合来看,研究构建的微信平台数据采集模块有效地挖掘出该科技大学的官方微信公众号的数据,并可以通过其特征分析结果给出其推广发展建议,在实际的微信平台的数据挖掘及行为特征分析中具备有效性。

The development of mobile Internet promotes the development of WeChat platform official account.In WeChat official account,strengthening data mining and feature analysis is the key to its rapid promotion.Based on this,the research uses crawler and other technologies to build the data collection module of the WeChat platform official account,and verifies it through experiments.The experimental results show that,according to the historical news released on the official WeChat official account of a university of science and technology,the number of single day releases of this account has reached 8 times in 8 years;In data mining,after removing more than 100001 content,the maximum number of reads is 91217,the number of likes is 1610,and the number of comments is 1027;At the same time,544 articles were published on Tuesday,accounting for 18.37%.To sum up,the WeChat platform data collection module built by the research can effectively mine the data of the official WeChat official account of the University of Science and Technology,and can give its promotion and development suggestions through its feature analysis results,which is effective in the data mining and behavior feature analysis of the actual WeChat platform.