Work

Analysis of adolescent social behavior on short video platforms based on graph neural networks

Year: 2025

Type: conference-paper

Abstract: To accurately analyze adolescent social behavior on short video platforms, a Graph Neural Network (GNN) model is employed to construct social network graphs and extract features, enabling modeling and classification of interactions and behavioral patterns among users. The study explores the process of node embedding and behavior pattern aggregation and updating. The results indicate that GNN outperforms traditional machine learning methods in identifying behavior patterns and classification tasks, achieving an accuracy of 87.6%, particularly excelling in handling sparse data and complex social network structures. This research provides strong support for optimizing platform algorithms and enhancing user experience.

Source: International Conference on Computer Technology, Information Engineering, and Electron Materials (CTIEEM)

DOI: 10.1117/12.3058733

Author: Yiming Wang

Institution: Sanda University

Language: English

Topic: Advanced Graph Neural Networks

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4409090349

FWCI:

Cites: 9

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Related to: 10