Campus Network Public Opinion Monitoring System Based on Reptile Technology

Tan, Yonghong; Lin, Qiang; Luan, Yu‐Xin; Chen, Tao; Qiao, Yifan; Luan, Yue

doi:10.1088/1755-1315/252/5/052136

Cited by 2 publications

(1 citation statement)

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“…At present, the research on these data includes hot spot discovery [2], crisis early warning, public opinion prediction [3], etc. Tan et al [4] analyzed the campus network public opinion, explored technologies, such as Chinese word segmentation and topic recognition, and combined analytical hierarchy process (AHP) with wavelet neural network to monitor the network public opinion. Taking the Sade event as an example, they found that the method had a good estimation accuracy.…”

Section: Introductionmentioning

confidence: 99%

Information Visualization Analysis of Public Opinion Data on Social Media

Feng¹,

Shi²

2021

IJCAI

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Section: Introductionmentioning

confidence: 99%

Information Visualization Analysis of Public Opinion Data on Social Media

Feng¹,

Shi²

2021

IJCAI

View full text Add to dashboard Cite

Modeling Multi-Dimensional Public Opinion Process Based on Complex Network Dynamics Model in the Context of Derived Topics

Chen

Yin

Yang

et al. 2021

Axioms

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With the rapid development of the Internet, the speed with which information can be updated and propagated has accelerated, resulting in wide variations in public opinion. Usually, after the occurrence of some newsworthy event, discussion topics are generated in networks that influence the formation of initial public opinion. After a period of propagation, some of these topics are further derived into new subtopics, which intertwine with the initial public opinion to form a multidimensional public opinion. This paper is concerned with the formation process of multi-dimensional public opinion in the context of derived topics. Firstly, the initial public opinion variation mechanism is introduced to reveal the formation process of derived subtopics, then Brownian motion is used to determine the subtopic propagation parameters and their propagation is studied based on complex network dynamics according to the principle of evolution. The formula of basic reproductive number is introduced to determine whether derived subtopics can form derived public opinion, thereby revealing the whole process of multi-dimensional public opinion formation. Secondly, through simulation experiments, the influences of various factors, such as the degree of information alienation, environmental forces, topic correlation coefficients, the amount of information contained in subtopics, and network topology on the formation of multi-dimensional public opinion are studied. The simulation results show that: (1) Environmental forces and the amount of information contained in subtopics are key factors affecting the formation of multi-dimensional public opinion. Among them, environmental forces have a greater impact on the number of subtopics, and the amount of information contained in subtopics determines whether the subtopic can be the key factor that forms the derived public opinion. (2) Only when the degree of information alienation reaches a certain level, will derived subtopics emerge. At the same time, the degree of information alienation has a greater impact on the number of derived subtopics, but it has a small impact on the dimensions of the final public opinion. (3) The network topology does not have much impact on the number of derived subtopics but has a greater impact on the number of individuals participating in the discussion of subtopics. The multidimensional public opinion dimension formed by the network topology with a high aggregation coefficient and small average path length is higher. Finally, a practical case verifies the rationality and effectiveness of the model proposed in this paper.

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Campus Network Public Opinion Monitoring System Based on Reptile Technology

Cited by 2 publications

References 1 publication

Information Visualization Analysis of Public Opinion Data on Social Media

Information Visualization Analysis of Public Opinion Data on Social Media

Modeling Multi-Dimensional Public Opinion Process Based on Complex Network Dynamics Model in the Context of Derived Topics

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