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<p>Exploring the influence of social networks on innovation and entrepreneurship of economics and management college students to help them better enhance their innovation consciousness to face the future social workplace. In this paper, the particle swarm algorithm is optimized according to the strategy and parameter adaptive mechanism, and the SPS-PSO algorithm is used to initialize and update the population. The social network and innovation and entrepreneurship ability of university students in economics and management are introduced, and feature selection based on strategy and parameter adaptive particle swarm algorithm is utilized. The index mining of social network and innovation and entrepreneurship ability of college students is conducted, and the data analysis of innovation and entrepreneurship ability of college students in economics and management is carried out with the example of the University of S. From the social network, the percentages of those who agree with the validity of social network centrality, heterogeneity, dynamics and linkage strength are 71.56, 71.69%, 72.55% and 71.16%, respectively. From the perspective of innovation and entrepreneurship, the overall percentage of college students in economics and management who agreed was 69.27%. This indicates that the higher the integrity of the social network structure of economics and management college students, the more it can enhance innovation and entrepreneurship abilities and promote the cultivation of observation and judgment ability and divergent thinking abilities of economics and management college students.</p>
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Exploring the influence of social networks on innovation and entrepreneurship of economics and management college students to help them better enhance their innovation consciousness to face the future social workplace. In this paper, the particle swarm algorithm is optimized according to the strategy and parameter adaptive mechanism, and the SPS-PSO algorithm is used to initialize and update the population. The social network and innovation and entrepreneurship ability of university students in economics and management are introduced, and feature selection based on strategy and parameter adaptive particle swarm algorithm is utilized. The index mining of social network and innovation and entrepreneurship ability of college students is conducted, and the data analysis of innovation and entrepreneurship ability of college students in economics and management is carried out with the example of the University of S. From the social network, the percentages of those who agree with the validity of social network centrality, heterogeneity, dynamics and linkage strength are 71.56, 71.69%, 72.55% and 71.16%, respectively. From the perspective of innovation and entrepreneurship, the overall percentage of college students in economics and management who agreed was 69.27%. This indicates that the higher the integrity of the social network structure of economics and management college students, the more it can enhance innovation and entrepreneurship abilities and promote the cultivation of observation and judgment ability and divergent thinking abilities of economics and management college students.

The influence of social network on innovation and entrepreneurship of economic and management college students based on adaptive particle swarm algorithm

Management and Law, Shaanxi University of Technology

Applied Mathematics and Nonlinear Sciences

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

Exploring the influence of social networks on innovation and entrepreneurship of economics and management college students to help them better enhance their...

The influence of social network on innovation and entrepreneurship of economic and management college students based on adaptive particle swarm algorithm

Online veröffentlicht: 09. Sept. 2023

Seitenbereich: -

Eingereicht: 23. Nov. 2022

Akzeptiert: 20. März 2022

DOI: https://doi.org/10.2478/amns.2023.2.00302

Schlüsselwörter
Particle swarm algorithm, Feature selection, SPS-PSO algorithm, Social network, Innovation and entrepreneurship

© 2023 Yan Huo, published by Sciendo

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

The influence of social network on innovation and entrepreneurship of economic and management college students based on adaptive particle swarm algorithm

Online veröffentlicht: 09. Sept. 2023

Seitenbereich: -

Eingereicht: 23. Nov. 2022

Akzeptiert: 20. März 2022

DOI: https://doi.org/10.2478/amns.2023.2.00302

SchlüsselwörterParticle swarm algorithm, Feature selection, SPS-PSO algorithm, Social network, Innovation and entrepreneurship

© 2023 Yan Huo, published by Sciendo

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

Schlüsselwörter
Particle swarm algorithm, Feature selection, SPS-PSO algorithm, Social network, Innovation and entrepreneurship