Open Access

Modeling of Student Group Public Opinion Dissemination Mechanism Based on Graph Convolutional Networks in Ideological and Political Education in Colleges and Universities

 and   
Sep 25, 2025

Cite
Download Cover

Figure 1.

SIR Process diagram
SIR Process diagram

Figure 2.

Process of method implementation
Process of method implementation

Figure 3.

Schematic diagram of the problem
Schematic diagram of the problem

Figure 4.

CNN-GCN Model application
CNN-GCN Model application

Figure 5.

The intervention level is level 0
The intervention level is level 0

Figure 6.

The intervention level is level 1
The intervention level is level 1

Figure 7.

The intervention level is level 2
The intervention level is level 2

Figure 8.

Reconstruction importance visualization
Reconstruction importance visualization

Figure 9.

Reconstruction importance visualization
Reconstruction importance visualization

The evolution of public opinion with Level 1

Peak (person) Peak time The peak of the network is the peak The peak of the line is the time of time The number of times is reduced to zero
Active person About 30,000 August 2nd About 40,000 August 5th August 10th
Neutral person About 50,000 August 5th About 90,000 August 5th August 10th
Negative person About 60,000 August 5th About 13,000 August 5th August 10th
Immune About 360,000 August 10th
Total About 300,000 August 5th August 10th

The intervention coefficient table

Intervention coefficient Corresponding parameter The intervention coefficient value of the intervention level is 1 The intervention coefficient value of the intervention level is 2
Learning rate intervention coefficient h 0.9 0.8
Infection rate intervention coefficient m 0.9 0.5
n 0.9 0.5
j 0.9 0.5
Conversion factor u 1.4 1.6
v 1.4 1.6
Immune rate intervention coefficient e 1.4 1.6
f 1.4 1.6
q 1.4 1.6
c 1.4 1.6

The evolution of public opinion with Level 0

Peak (person) Peak time The peak of the network is the peak The peak of the line is the time of time The number of times is reduced to zero
Susceptible About 300,000 August 1st
Active person About 50,000 August 2nd About 70,000 August 5th August 10th
Neutral person About 70,000 August 5th About 10,000 August 5th August 10th
Negative person About 110,000 August 5th About 15,000 August 5th August 10th
Immune About 350,000 August 10th
Total About 40,000 August 5th August 10th

Parameter value

Parameter Value Parameter Value Parameter Value
U 1.2 S 0.002 P 0.001
G 0.002 N 0.002 R 0.001
h 0.16 m 0.16 n 0.15
j 0.25 e 0.03 f 0.03
q 0.03 c 0.15 x 1.6
y 1.5 z 2.5 u 0.02
v 0.03

The comparison results of the model and the benchmark model are compared

Reference model Acc. NR FR TR UR
F1 F1 F1 F1
DTC 0.458 0.663 0.406 0.395 0.45
SVM-TS 0.55 0.75 0.413 0.585 0.547
SVM-TK 0.635 0.631 0.612 0.781 0.667
MVAE 0.649 0.551 0.682 0.711 0.58
RvNN 0.739 0.647 0.768 0.838 0.717
PPC 0.878 0.818 0.914 0.824 0.819
GCAN 0.789 0.748 0.744 0.942
VAE-GCN 0.862 0.798 0.805 0.981 0.894
BI-GCN 0.896 0.814 0.848 0.936 0.837
GLAN 0.911 0.918 0.853 0.843 0.953
HGATRD 0.934 0.972 0.915 0.989 0.894
Our method 0.993 0.937 0.904 0.849 0.935

Comparison with the actual public opinion

Is it shown Public opinion Public opinion peak The peak time of public opinion Whether the peak is reduced quickly The time of the ttie is zero
SIR Model × Three days earlier Obviously small The same × Six days earlier
Ours Three days earlier The same The same Five days earlier
Language:
English