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机构地区:[1]大连外国语大学软件学院,辽宁 大连
出 处:《新闻传播科学》2023年第2期284-290,共7页Journalism and Communications
摘 要:本文利用python语言,结合第三方库requests、jieba和snownlp对知乎社交平台的大学生综合素质测评讨论话题进行数据爬取和情感倾向分析。首先,在数据获取方面,本文使用爬虫工具共收集了约1000条评论,并将其分为积极和消极两类。其次,通过数据可视化方法分析了学生们对于综合素质测评分数产生的意见和态度。最后,运用词频统计方法总结了学生们关注的问题,并提出了实施更加公平公正的综合测评方案的建议。In this paper, we use the Python language and third-party libraries, including requests, jieba, and snownlp, to crawl data and perform sentiment analysis on discussions related to the comprehensive quality evaluation of college students on the Zhihu social platform. Firstly, for data acquisition, we collected around 1000 comments using a web crawler tool and categorized them into positive and negative categories. Secondly, using data visu-alization methods, we analyzed the opinions and attitudes of students towards the comprehensive quality assessment scores. Finally, we summarized the students’ concerns using the word frequency statistical method and proposed suggestions for implementing a fair and just comprehensive eval-uation scheme.
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