Ying Lou | Searcharxiv

arXiv2025

Mapping Academic Integrity: Global Retraction Trends Explored through a Topic Lens

Scientific publications have long served as the cornerstone of innovation, exhibiting stable growth over the years. Recently, however, retractions have surged dramatically, driven largely by the proliferation of low-quality and fraudulent articles, posing a substantial threat to research integrity. By integrating annual publication and retraction data, this study employs the relative retraction rate (R3) to systematically examine disparities and evolving trends from a topical perspective. Our analysis reveals that the number of retractions has grown significantly faster than that of global publications, yielding an overall retraction rate of 0.12%. While retractions occur across all disciplines, substantial disparities exist, ranging from 0.035% in Physics to 0.34% in Computer Science. This gap widens at finer levels of granularity, reaching roughly 8.99% in Human-Computer Interaction. Moreover, unusually high R3 values frequently coincide with rapid publication growth in specific fields. We also developed Retraction Monitor, a web application for monitoring retraction dynamics across diverse fields, enabling stakeholders to visualize these trends and assess risks to research integrity. These findings provide valuable insights for identifying high-risk fields and developing tailored governance policies to strengthen research rigor and mitigate field-specific retraction risks.

cs.DL↗

arXiv2025

The Landscape of problematic papers in the field of non-coding RNA

Retractions have increased sharply in recent years, alongside a growing number of papers that receive post-publication comments questioning their reliability (commented papers). Together, retracted and commented papers undermine the credibility of scientific research and may also threaten public health. In this study, we examine problematic papers in the field of non-coding RNA (ncRNA) from multiple perspectives to identify common patterns and inform strategies for addressing large-scale fraudulent publications. We find that studies on under-investigated ncRNAs are more likely to become problematic papers. These papers often show substantial textual similarity, and many additional papers with similar text also display suspicious image duplication. Healthcare institutions, particularly those with lower publication output, appear especially vulnerable to producing such papers. Most problematic papers are concentrated in a small set of journals, many of which do not adequately address concerns raised after publication. Overall, our findings indicate that a substantial number of problematic papers may remain undetected and that their shared characteristics can support more effective strategies for identifying and curbing large-scale fraudulent publications.

cs.DL↗