| 陈荣,赵冰燕,李建霞,严素梅.面向数据治理的主体注意力趋同分析模型及实证研究[J].数字图书馆论坛,2025,21(6):10~20 |
| 面向数据治理的主体注意力趋同分析模型及实证研究 |
| Model for Analyzing Convergence of Attention Among Data Governance Entities and Empirical Research |
| 投稿时间：2025-05-17 |
| DOI：10.3772/j.issn.1673-2286.2025.06.002 |
| 中文关键词: 数据治理；主体；注意力趋同；趋同分析；动态演化；健康医疗 |
| 英文关键词: Data Governance; Entity; Attention Convergence; Convergence Analysis; Dynamic Evolution; Health Care |
| 基金项目: |
| 作者 | 单位 | | 陈荣 | 华东理工大学科技信息研究所；华东理工大学商学院 | | 赵冰燕 | 华东理工大学科技信息研究所；华东理工大学商学院 | | 李建霞 | 华东理工大学科技信息研究所；华东理工大学商学院 | | 严素梅 | 华东理工大学科技信息研究所；华东理工大学商学院 |
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| 中文摘要: |
| 数据治理是数据价值得以充分挖掘与应用的关键，其效能提升需要多主体共同参与。数据治理主体注意力趋同研究主要探究主体关注内容的一致性，对优化数据协同治理体系、保障数据治理的有效性具有重要参考价值。以BERTopic模型和加权关键词主题趋同度计算为基础，构建面向数据治理域的主体注意力趋同分析模型，利用该模型对代表特定领域数据治理主体注意力的数据进行主题建模与趋同度计算，根据主体注意力演化结果剖析主体注意力分配的差异，在此基础上计算主体注意力趋同度，以量化分析相关领域数据治理主体注意力趋同现状。该分析模型为相关决策者了解数据治理主体注意力的变化趋势提供了分析框架与评价维度。以健康医疗领域为例进行实证研究，结果表明：该领域主体在数据管理体系方面的注意力趋同度较高，聚焦于数据管理与数据安全、数据共享等；在数据价值体系方面的注意力趋同度整体较低，主要关注数据质量与服务评价。 |
| 英文摘要: |
| Data governance is the key to fully unlocking and leveraging the value of data, and its effectiveness enhancement requires the collaborative participation of multiple entities. Research on the convergence of attention among data governance entities primarily explores the consistency of their focus areas, offering significant reference value for optimizing collaborative data governance systems and ensuring the effectiveness of data governance. Based on the BERTopic model and weighted keyword topic convergence calculation, this study constructs an attention convergence analysis model tailored to the data governance domain. This model is used to perform topic modeling and convergence calculation on data representing the attention of data governance entities in a specific field. By analyzing the differences in attention allocation based on the evolution of entity attention, the model calculates the convergence degree of entity attention, thereby quantitatively assessing the current state of attention convergence among data governance entities in the relevant field. This analysis model provides decision-makers with an analytical framework and evaluation dimensions to understand the trends in the attention of data governance entities.Taking the healthcare sector as an example, the study indicates that entities in this sector exhibit a high degree of attention convergence in data management systems, focusing on data management, data security, and data sharing. However, attention convergence degree in data value systems is generally low, with primary focus on data quality and service evaluation. |
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