sis 24(3):

Research Article

Survey and Analysis of Citizen Network Political Participation Based on Binary Search Tree Algorithm

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  • @ARTICLE{10.4108/eetsis.4922,
        author={Haixia Li},
        title={Survey and Analysis of Citizen Network Political Participation Based on Binary Search Tree Algorithm},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={11},
        number={3},
        publisher={EAI},
        journal_a={SIS},
        year={2024},
        month={2},
        keywords={binary search tree algorithm, civic networks, political engagement, data analysis, social media interaction},
        doi={10.4108/eetsis.4922}
    }
    
  • Haixia Li
    Year: 2024
    Survey and Analysis of Citizen Network Political Participation Based on Binary Search Tree Algorithm
    SIS
    EAI
    DOI: 10.4108/eetsis.4922
Haixia Li1,*
  • 1: Xi'an Shiyou University
*Contact email: haixia2022@xsyu.edu.cn

Abstract

NTRODUCTION: In the digital age, citizens' online political engagement is crucial for the development and stability of society. OBJECTIVES: To gain insights into and address the challenges facing political engagement today, where effectively assessing and promoting citizen participation in the context of the information explosion and the popularization of social media has become a pressing issue. METHODS: Using the binomial search tree algorithm, which was introduced to analyze and predict citizens' political behaviors in the online environment, able to dig deeper into citizens' concerns, opinions, and interaction patterns on political topics by collecting large-scale online data and applying it to the binomial search tree algorithm. RESULTS: The binary search tree algorithm is able to efficiently and accurately reveal the complex features of citizens' online political engagement. CONCLUSION: The binomial search tree algorithm is more advantageous than traditional methods, providing deeper insights for government policymakers and social scientists, and this study is essential for advancing the understanding and enhancement of citizens' online political engagement.