[Purpose/Significance] A systematic research on the key factors and their underlying mechanism that influence the level of government open data empowerment can drive a virtuous cycle, shifting data usage from passive opening and simple utilization to proactive empowerment and benefit transformation. [Result/Conclusion] A grey relational analysis (GRA) model was used to identify the key factors affecting the empowerment level of government open data, and to quantitatively analyze the degree of association between these factors and empowerment indicators. Based on this, social network analysis (SNA) was employed to construct a “factor-indicator” association network, systematically revealing the interaction relationships among various elements. Ultimately, a structural diagram of the factors influencing government open data empowerment was developed. [Result/Conclusion] The study finds that “data source diversity” is at the core of the influence network, as its ability to integrate multi-source data serves as the foundation for the empowerment ecosystem. “Data accessibility” occupies a structural hole position in the data structure, connecting both supply and demand ends through diverse data formats, significantly improving resource circulation efficiency. “Number of data interfaces” and “data continuity” are key levers: the former lowers development barriers, while the latter ensures data timeliness, jointly driving application innovation. It provides theoretical references for enhancing the empowerment potential of government open data and maximizing its social and economic benefits.
Duan Yaoqing
,
Wang Xiaoxi
,
Li Yanru
. Research on Influencing Factors of Government Open Data Empowerment Level in China Based on Correlation Analysis[J]. Library and Information Service, 2026
, 70(7)
: 118
-130
.
DOI: 10.13266/j.issn.0252-3116.2026.07.008
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