新型冠状病毒肺炎疫情微博数据分析

The Analysis of Weibo Data about COVID-19 Epidemic

现在全球都在抗击新型冠状病毒肺炎,新闻媒体实时发布疫情新闻,人们时刻关注疫情发展情况。本文基于微博平台,以"新冠肺炎最新动态"、"疫情"、"新冠疫苗"作为关键字,采用后羿采集器爬虫软件爬取微博平台关于新冠疫情近期博文数据。在Python平台对文本数据进行预处理,删除无意义字符,用Jieba库进行精确分词,统计词频并排序,将词频较高的前800个词语用WordCloud生成词云。结果表明,近期微博网民的情绪受到境外疫情影响,对疫情形势的关注度较高。

Now COVID-19 is being fought globally,the news media releases the epidemic news in real time,and people keep an eye on the situation of the epidemic.Using three keywords,i.e.,COVID-19 Latest Update,Epidemics,and COVID-19 Vaccine,this paper crawls the blog data about COVID-19 in the recent three months on the Weibo platform by using Houyi crawler software.The text data are processed firstly in the python platform,meaningless characters are removed,words are accurately divided by Jieba library,then the word frequency is counted and sorted,the word cloud of 800 words with higher word frequency is generated by WordCloud.The result shows that the recent mood of people is affected by the epidemic situation abroad,and people are paying high attention to the situation of the epidemic.