<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper describes the dynamic propagation process of the influence of public service advertisements (PSAs) using the information dissemination model and proposes a click probability function by modeling the click rate of advertisements, which is solved by a heuristic method. The EPR advertisement recommendation algorithm is selected to simulate the push process of the advertisement, and the experimental performance is analyzed. Analyze the presentation of Shaanxi regional culture and the network mobilization mechanism model of enterprise public service advertisement, predict and analyze the click rate of public service advertisement broadcasting, and emphasize the trust analysis of the audience. Variables such as the number of effective viewing of advertisements, the number of link clicks, the number of likes, and the amount of placement are selected to carry out descriptive analysis and correlation analysis of the effect of PSAs on Shaanxi regional culture. From the correlation coefficient matrix, it can be seen that the correlation coefficients between the explanatory variables take smaller values and are at the level below 0.11, and the number of likes has significant positive correlation coefficients with the indicators of advertisement effect at each stage. Thus it can be verified that the social attributes of advertisements play a positive role in the effect of advertisements.</p>
</abstract>

This paper describes the dynamic propagation process of the influence of public service advertisements (PSAs) using the information dissemination model and proposes a click probability function by modeling the click rate of advertisements, which is solved by a heuristic method. The EPR advertisement recommendation algorithm is selected to simulate the push process of the advertisement, and the experimental performance is analyzed. Analyze the presentation of Shaanxi regional culture and the network mobilization mechanism model of enterprise public service advertisement, predict and analyze the click rate of public service advertisement broadcasting, and emphasize the trust analysis of the audience. Variables such as the number of effective viewing of advertisements, the number of link clicks, the number of likes, and the amount of placement are selected to carry out descriptive analysis and correlation analysis of the effect of PSAs on Shaanxi regional culture. From the correlation coefficient matrix, it can be seen that the correlation coefficients between the explanatory variables take smaller values and are at the level below 0.11, and the number of likes has significant positive correlation coefficients with the indicators of advertisement effect at each stage. Thus it can be verified that the social attributes of advertisements play a positive role in the effect of advertisements.

A Study on the Presentation and Communication Influence of Shaanxi Regional Culture in Public Service Advertisements from the Perspective of Social Network Analysis

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper describes the dynamic propagation process of the influence of public service advertisements (PSAs) using the information dissemination model and...

A Study on the Presentation and Communication Influence of Shaanxi Regional Culture in Public Service Advertisements from the Perspective of Social Network Analysis

Online veröffentlicht: 06. Dez. 2023

Seitenbereich: -

Eingereicht: 27. Feb. 2023

Akzeptiert: 16. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01393

Schlüsselwörter
Independent cascade model, Linear threshold model, EPR algorithm, Correlation analysis, Shaanxi regional culture

© 2023 Ying Ma, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A Study on the Presentation and Communication Influence of Shaanxi Regional Culture in Public Service Advertisements from the Perspective of Social Network Analysis

Online veröffentlicht: 06. Dez. 2023

Seitenbereich: -

Eingereicht: 27. Feb. 2023

Akzeptiert: 16. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01393

SchlüsselwörterIndependent cascade model, Linear threshold model, EPR algorithm, Correlation analysis, Shaanxi regional culture

© 2023 Ying Ma, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Independent cascade model, Linear threshold model, EPR algorithm, Correlation analysis, Shaanxi regional culture