基于文本挖掘的信息传输效果研究

Yuting Sun
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摘要

桑斯坦提出,在信息传播过程中,受公众自身信息需求和利益导向的影响,人们只关注让自己感觉舒服的信息领域。久而久之,人们就会把自己束缚在 "茧房 "这样的茧中,桑斯坦称之为 "信息茧房"。微博作为一种新兴的开放式社交媒体,在为用户提供信息分享和传播便利的同时,也创造了一个个性化的社交空间。基于此,本文通过文本挖掘技术对微博中的话题进行文本挖掘,旨在研究舆情的传播规律。对于任务一,本文使用爬虫技术访问微博搜索端api接口,代码使用python请求包,从而确定访问接口并抓取数据。之后,本文使用 jieba 库进行正则表达式和中文分词,并构建词云图进行统计分析。最后,本文通过词频数定量描述了话题的传播过程,并分析了其影响因素。对于任务 2,本文将该问题视为典型的评价问题。因此,本文构建了 AHP 层次分析法模型对其进行求解,并构建专家评价矩阵对其进行打分评价,从而得出这些因素的影响程度。
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Research on the Effect of Information Transmission based on Text Mining
Sangstan proposed that, in the process of information dissemination, people only focus on the information field that makes them feel comfortable due to the influence of the public's own information needs and interest guidance. As time passes, they will shackle themselves to the cocoon like "cocoon room", which Sangstan called "information cocoon room". As an emerging open social media, microblog provides users with the convenience of information sharing and dissemination, and also creates a personalized social space. Based on this, this paper conducts text mining on topics in microblog through text mining technology, aiming to study the propagation law of public opinion. For Task 1, this paper uses the crawler technology to access the microblog search end api interface, and the code uses the python request package, so that the access interface can be determined and the data can be crawled. After that, this paper uses the jieba library to carry out regular expression and Chinese word segmentation, and constructs a word cloud map for statistical analysis. Finally, it quantitatively describes the spread process of topics through the number of word frequencies, and analyzes its influencing factors. For Task 2, this paper considers this problem as a typical evaluation problem. Therefore, this paper constructs the AHP analytic hierarchy process model to solve it, and constructs the expert evaluation matrix to score and evaluate it, so as to get the influence of these factors.
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