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基于python的博物馆大众满意度评价
2019-08-20  

  黄晓东  石瀚臣
  (北京联合大学应用文理学院,北京,100191)
  摘 要:随着中国经济的不断发展,北京作为我国的文化中心,大众的文化消费水平在不断提高。博物馆作为大众最为喜爱的文化消费方式之一,参观量不断提高。同时,随着互联网时代的到来,互联网越来越成为大众生活中不可或缺的事物。微博作为当下最为热门的互联网社交软件之一,大量用户通过发表微博记录对生活的感受,微博文本数量庞大。本文将通过python进行数据抓取,抓取不同类型的博物馆微博文本,并以此为基础进行情感分析,计算出大众对于博物馆情感倾向,并将评价数值予以分类。并通过博物馆、季节和区县的角度,对情感分析的结果进行分析。
  关键词:数据抓取;微博文本;博物馆;情感分析;情感倾向
  Public satisfaction evaluation of museums based on Python
  Abstract: With the continuous development of China's economy, Beijing, as the cultural center of China, the level of cultural consumption of the public is constantly improving. As one of the most popular cultural consumption methods of the public, the museum has continuously increased its number of visits. At the same time, with the advent of the Internet age, the Internet has become an indispensable part of the public life. As one of the most popular Internet social softwares, Weibo has a large number of users who have expressed their feelings about life through Weibo. This article will use Python to capture data, capture different types of museum microblog texts, and use this as a basis for sentiment analysis, calculate the public's emotional tendency towards the museum, and classify the evaluation values. The results of sentiment analysis are analyzed through the perspectives of museums, seasons and districts.
  Keywords: data capture;microblog text; museum; sentiment analysis; sentiment orientation
   

 

 

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