Exploring Structural Dynamics in Retracted and Non-Retracted Author's Collaboration Networks: A Quantitative Analysis

TL;DR

This study compares the structural properties of collaboration networks in retracted versus non-retracted scientific papers, revealing distinct network patterns that could inform research integrity policies.

Contribution

It provides a quantitative analysis of collaboration network differences between retracted and non-retracted papers, highlighting structural risk factors associated with retractions.

Findings

Retracted networks are more hierarchical and centralized.

Non-retracted networks show higher clustering and connectivity.

Significant differences in Degree Centrality and Weighted Degree metrics.

Abstract

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.