Vol. 3 No. 2 (2025)

View Vol. 3 No. 2 (2025)

All articles published in this issue have undergone a thorough peer review process, and stringent checks for repetition rates have been implemented to ensure the integrity of the content.

Total number of articles in this issue: 5
Total number of pages in this issue: 51

For inquiries regarding the content of specific articles, please feel free to contact the respective authors via their provided email addresses. For questions related to the journal itself, please reach out directly to SUAS Press.

Published: 2025-03-18

Articles

  • Real-time Cross-border Payment Fraud Detection Using Temporal Graph Neural Networks: A Deep Learning Approach
    Authors: Chengru Ju, Xiaowen Ma, Boyang Dong
    Resource Type: Article
    Disciplines: Business | Subjects: Finance
    Publication ID: v3n2a01
    Abstract: The rapid expansion of digital payments across borders has led to increased risks in the financial system, especially in the fraud process. Traditional methods show limitations in capturing the spatial-temporal patterns inherent in crossing...
    1-12
    DOI Icon Abstract views: 184 | DOI Icon PDF downloads: 95 | DOI Icon references: 32
    DOI Icon DOI: 10.70393/616a736d.323639
    DOI Icon ARK: ark:/40704/AJSM.v3n2a01
  • Deep Learning-Based Analysis of Social Media Sentiment Impact on Cryptocurrency Market Microstructure
    Authors: Yining Zhang, Jiayan Fan, Boyang Dong
    Resource Type: Article
    Disciplines: Business | Subjects: Finance
    Publication ID: v3n2a02
    Abstract: This paper presents an advanced framework for analyzing cryptocurrency market microstructure through the integration of deep learning techniques and social media sentiment analysis. The proposed approach combines BERT-based sentiment analysis with...
    13-21
    DOI Icon Abstract views: 73 | DOI Icon PDF downloads: 31 | DOI Icon references: 27
    DOI Icon DOI: 10.70393/616a736d.323730
    DOI Icon ARK: ark:/40704/AJSM.v3n2a02
  • Semantic Network Analysis of Financial Regulatory Documents: Extracting Early Risk Warning Signals
    Authors: Yibang Liu, Wenyu Bi, Jiayan Fan
    Resource Type: Article
    Disciplines: Economics | Subjects: Behavioral Economics
    Publication ID: v3n2a03
    Abstract: This paper presents a semantic network analysis framework for extracting early risk warning signals from financial regulatory documents. Financial regulations contain critical information about emerging risks, but their increasing volume and...
    22-32
    DOI Icon Abstract views: 45 | DOI Icon PDF downloads: 16 | DOI Icon references: 32
    DOI Icon DOI: 10.70393/616a736d.323731
    DOI Icon ARK: ark:/40704/AJSM.v3n2a03
  • A Differential Privacy-Based Mechanism for Preventing Data Leakage in Large Language Model Training
    Authors: Xingpeng Xiao, Yaomin Zhang, Heyao Chen, Wenkun Ren, Junyi Zhang, Jian Xu
    Resource Type: Article
    Disciplines: Management | Subjects: Human Resource Management
    Publication ID: v3n2a04
    Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks, yet they face significant challenges in protecting sensitive information during training. This paper presents a novel differential...
    33-42
    DOI Icon Abstract views: 51 | DOI Icon PDF downloads: 24 | DOI Icon references: 19
    DOI Icon DOI: 10.70393/616a736d.323732
    DOI Icon ARK: ark:/40704/AJSM.v3n2a04
  • Anomalous Payment Behavior Detection and Risk Prediction for SMEs Based on LSTM-Attention Mechanism
    Authors: Xingpeng Xiao, Heyao Chen, Yaomin Zhang, Wenkun Ren, Jian Xu, Junyi Zhang
    Resource Type: Article
    Disciplines: Business | Subjects: Finance
    Publication ID: v3n2a05
    Abstract: This paper proposes a novel approach for detecting anomalous payment behaviors and predicting financial risks in Small and Medium-sized Enterprises (SMEs) using an enhanced LSTM-Attention mechanism. The model integrates bi-directional LSTM...
    43-51
    DOI Icon Abstract views: 29 | DOI Icon PDF downloads: 19 | DOI Icon references: 8
    DOI Icon DOI: 10.70393/616a736d.323733
    DOI Icon ARK: ark:/40704/AJSM.v3n2a05