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

Fuente: arXiv
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Auteurs principaux: Sharma, Kiran, Sharma, Aanchal, Jose, Jazlyn, Saini, Vansh, Sobti, Raghavraj, Uddin, Ziya
Format: Preprint
Publié: 2024
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author Sharma, Kiran
Sharma, Aanchal
Jose, Jazlyn
Saini, Vansh
Sobti, Raghavraj
Uddin, Ziya
author_facet Sharma, Kiran
Sharma, Aanchal
Jose, Jazlyn
Saini, Vansh
Sobti, Raghavraj
Uddin, Ziya
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2411_17447
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Exploring Structural Dynamics in Retracted and Non-Retracted Author's Collaboration Networks: A Quantitative Analysis
Sharma, Kiran
Sharma, Aanchal
Jose, Jazlyn
Saini, Vansh
Sobti, Raghavraj
Uddin, Ziya
Information Retrieval
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.
title Exploring Structural Dynamics in Retracted and Non-Retracted Author's Collaboration Networks: A Quantitative Analysis
topic Information Retrieval
url https://arxiv.org/abs/2411.17447