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

<p>With the development of digitalization and Internet technology, algorithm-driven international Chinese online language and culture dissemination mechanisms are becoming increasingly important and a key area of cultural exchange in globalization. This study explores the international Chinese online language and culture communication mechanism under algorithm-driven. By analyzing social network data and adopting quantitative methods such as the SEIR model, the study reveals the effects of network structure, user behavior and cultural content characteristics on communication. The study results show that in the algorithm-optimized network environment, the propagation speed of information is increased by about 50%, and the propagation efficiency of its central node is increased by nearly 70%. Simulations using the SEIR model show that the dissemination coverage of Chinese culture can be increased by more than 40% in a short period with the intervention of the algorithm. In addition, the survey data shows that about 60% of the respondents consider social media the main channel to learn about Chinese culture. The study also found that content with a high degree of interactivity is more likely to be disseminated, with an average interaction rate 30% higher than that of moderate content. Algorithm-driven Chinese cultural communication has higher speed and breadth, but it also needs to pay attention to the depth and diversity of cultural content.</p>
</abstract>

With the development of digitalization and Internet technology, algorithm-driven international Chinese online language and culture dissemination mechanisms are becoming increasingly important and a key area of cultural exchange in globalization. This study explores the international Chinese online language and culture communication mechanism under algorithm-driven. By analyzing social network data and adopting quantitative methods such as the SEIR model, the study reveals the effects of network structure, user behavior and cultural content characteristics on communication. The study results show that in the algorithm-optimized network environment, the propagation speed of information is increased by about 50%, and the propagation efficiency of its central node is increased by nearly 70%. Simulations using the SEIR model show that the dissemination coverage of Chinese culture can be increased by more than 40% in a short period with the intervention of the algorithm. In addition, the survey data shows that about 60% of the respondents consider social media the main channel to learn about Chinese culture. The study also found that content with a high degree of interactivity is more likely to be disseminated, with an average interaction rate 30% higher than that of moderate content. Algorithm-driven Chinese cultural communication has higher speed and breadth, but it also needs to pay attention to the depth and diversity of cultural content.

Research on Algorithm-Driven International Chinese Online Language and Culture Dissemination Mechanisms

Applied Mathematics and Nonlinear Sciences

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

With the development of digitalization and Internet technology, algorithm-driven international Chinese online language and culture dissemination mechanisms are...

Research on Algorithm-Driven International Chinese Online Language and Culture Dissemination Mechanisms

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 17. Jan. 2024

Akzeptiert: 22. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0669

Schlüsselwörter
International Chinese language, Algorithm-driven, Social network analysis, SEIR modeling

© 2024 Yingbo Li, published by Sciendo

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

Research on Algorithm-Driven International Chinese Online Language and Culture Dissemination Mechanisms

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 17. Jan. 2024

Akzeptiert: 22. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0669

SchlüsselwörterInternational Chinese language, Algorithm-driven, Social network analysis, SEIR modeling

© 2024 Yingbo Li, published by Sciendo

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

Schlüsselwörter
International Chinese language, Algorithm-driven, Social network analysis, SEIR modeling