分析撤稿论文的作者合作网络结构，发现其更集中、层级化。
Exploring Structural Dynamics in Retracted and Non-Retracted Author's Collaboration Networks: A Quantitative Analysis
- 构建作者合作网络，对比撤稿与未撤稿论文的结构差异。
- 撤稿论文网络中心度更高，连接更集中，聚类强度更低。
- 为提升科研诚信提供数据支持，适合科研管理者参考。
撤稿损害科学文献的可信度和未来研究基础。分析撤稿论文的合作网络可识别风险因素，如重复出现的合作者或机构。本研究基于Retraction Watch和Scopus数据，选取30位有重大撤稿记录的作者，构建合作网络并分析其结构特性。结果显示，撤稿论文网络呈现层级化、中心化特征，而非撤稿论文则表现出分布式协作，具有更强的聚类性和连通性。通过t检验和Cohen's d效应量分析，度中心性和加权度等指标在两类网络间存在显著差异，揭示了易引发撤稿的合作模式。这些发现有助于制定政策以提升科研诚信。
原文摘要 · Abstract (English)
Retractions undermine the reliability of scientific literature and the foundation of future research. Analyzing collaboration networks in retracted papers can identify risk factors, such as recurring co-authors or institutions. This study compared the network structures of retracted and non-retracted papers, using data from Retraction Watch and Scopus for 30 authors with significant retractions. Collaboration networks were constructed, and network properties analyzed. Retracted networks showed hierarchical and centralized structures, while non-retracted networks exhibited distributed collaboration with stronger clustering and connectivity. Statistical tests, including $t$-tests and Cohen's $d$, revealed significant differences in metrics like Degree Centrality and Weighted Degree, highlighting distinct structural dynamics. These insights into retraction-prone collaborations can guide policies to improve research integrity.
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