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Academic Journal of Computing & Information Science, 2022, 5(2); doi: 10.25236/AJCIS.2022.050206.

Construction of Early Warning Mechanism of Network Public Opinion in Colleges and Universities under Big Data Environment

Author(s)

Run Xi

Corresponding Author:
Run Xi
Affiliation(s)

Sichuan Vocational and Technical College, Suining, China

Abstract

With the advent of the data age, everyone is in the torrent of information. At the same time, with the development and popularization of the Internet, information exchanges between people have become more convenient and faster, and the resulting early warning of network public opinion (NPO) has become an object we have to pay attention to. For colleges and universities, the construction of network public opinion warning (NPOW) is of great significance. This research aims to study the construction of NPO early warning mechanism in colleges and universities under the big data environment. Based on the understanding of the relevant theories of NPO, this article first explains the construction goals and principles of the early warning mechanism of NPO in colleges and universities, and uses a questionnaire survey method to study the necessity and effect of establishing an early warning mechanism of NPO in colleges and universities, and proposes Countermeasures that universities can refer to when constructing an early warning mechanism for NPO. According to the questionnaire "Do you think the school needs to provide early warning of NPO", 10.7% of college students indicated that it is unnecessary. 15.84% of college students think that it doesn't matter to give early warning of NPO, which shows that the current colleges and universities lack in-depth understanding of early warning of NPO.

Keywords

Big Data; Network Public Opinion; Early Warning Mechanism; Mechanism Construction

Cite This Paper

Run Xi. Construction of Early Warning Mechanism of Network Public Opinion in Colleges and Universities under Big Data Environment. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 2: 35-40. https://doi.org/10.25236/AJCIS.2022.050206.

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