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CNN ‐based politics public opinion analysis of undergraduates: A case study with CDN deployment
Author(s) -
Xie Yuchi
Publication year - 2021
Publication title -
internet technology letters
Language(s) - English
Resource type - Journals
ISSN - 2476-1508
DOI - 10.1002/itl2.287
Subject(s) - public opinion , software deployment , politics , government (linguistics) , convolutional neural network , computer science , public relations , political science , data science , artificial intelligence , law , linguistics , philosophy , operating system
In the era of social media, the political speech of undergraduates blots out the sky and covers up the earth, which perhaps generates the negative effect. To enhance the management ability of government departments, it is considerably necessary to pay more attention to the public opinion. However, the current researches on the public opinion mainly focus on mathematical modeling or data mining irrespective of public opinion analysis. Consider that Convolutional Neural Network (CNN) has the strong data analysis ability, this paper uses CNN to realize the special application, that is, politics public opinion analysis of undergraduates, which has two functions. On one hand, greatly help the government departments eliminate the crisis timely; On the other hand, correctly guide the political education of undergraduates. Besides, this paper also presents a case study based on Content Delivery Network (CDN) deployment, in which a monitor system of public opinion analysis is implemented to analyze the undergraduates' political speech. Finally, with three public opinion dissemination modes consideration, the experiments are made. The results show that CNN has better training ability and the whole deployment is more significant compared to the state‐of‐the‐art schemes.