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Open Access

Measurement and Network Analysis for the Data Service Market Based on Heterogeneous Multi-Agent Modeling

Deyu Zhou1,2Yuwei Guo3Xudong Lu1,2Linhao Zhang1,2Wei Guo1,2Lizhen Cui1,2( )
School of Software, Shandong University, Jinan 250101, China
Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan 250101, China
College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
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Abstract

With the increasing complexity of collaboration among various social entities and user demands, the factors affecting the stable development of the data service market are also growing. These factors include the widespread dissemination of information enhancing subjective consciousness, the continuous improvement in intelligence, and the complexification of structural relationships. To achieve effective governance and regulation of the data service market, it is crucial to conduct simulation experiments before making regulatory decisions. However, current research and analysis of the data service market primarily focus on data-level performance, proving inadequate when it comes to measurement and analysis of multiple heterogeneous entities and the integration of various social elements within the data service market. Based on this, this paper innovatively proposes a data service market measurement and network analysis method based on heterogeneous multi-agent modeling. By introducing the service ecosystem theory, we clarify the participants and external factors of the data service market and conduct utility measurements for three-level entities based on value creation. Furthermore, an analytical methodology is devised to precisely assess the influence of heterogeneous networks on utility. Finally, the paper verifies the effectiveness of the proposed method through the analysis of experimental results.

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International Journal of Crowd Science
Pages 67-77

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Cite this article:
Zhou D, Guo Y, Lu X, et al. Measurement and Network Analysis for the Data Service Market Based on Heterogeneous Multi-Agent Modeling. International Journal of Crowd Science, 2026, 10(2): 67-77. https://doi.org/10.26599/IJCS.2025.9100001

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Received: 27 September 2024
Revised: 14 December 2024
Accepted: 03 January 2025
Published: 11 June 2026
© The author(s) 2026.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).