arXiv subjects

Hui-Zhen Fu

Publications and source records attributed to Hui-Zhen Fu.

5 recordsLinked to original sources

arXiv2026

Science discussions of retracted articles on Bluesky: public scrutiny or misinformation spreading?

Post-publication peer review (PPPR) has emerged as an important supplement to traditional peer review, with social media playing a growing role in publicising potential problems in published research. However, it remains unclear whether social media discussions of retracted articles primarily reflect good practices, such as exposing flaws and acknowledging retraction status, or bad practices, such as overlooking retractions and continuing to disseminate scientific misinformation. In this study, we collected Bluesky posts referencing scholarly articles from Altmetric and retrieved metadata for the referenced articles using OpenAlex. The final dataset included 284 retracted articles with 79 pre-retraction posts and 857 post-retraction posts, 59 retraction notices with 186 posts, and 609,461 non-retracted articles with 1,344,756 posts. We manually coded Bluesky posts discussing retracted articles to identify instances of good and bad practice. The results show that posts demonstrating good practice (89.9%) substantially outnumbered those demonstrating bad practice (10.1%). Posts reflecting good practice also had more user engagement. In the pre-retraction phase, good practice posts constituted a slight minority (43.0%), whereas in the post-retraction phase they were dominant (94.2%). Most negative posts in the pre-retraction phase (90.0%) had good practice while only 17.3% positive posts in the post-retraction phase showed bad practice. Thus, sentiment analysis can be helpful to filter posts that could flag potential flaws before retraction, but it may struggle to accurately identify the spread of misinformation after retraction. More broadly, this study highlights the potential of Bluesky to support responsible scientific communication, public scrutiny, and research integrity.

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arXiv2025

Do male leading authors retract more articles than female leading authors?

Scientific retractions reflect issues within the scientific record, arising from human error or misconduct. Although gender differences in retraction rates have been previously observed in various contexts, no comprehensive study has explored this issue across all fields of science. This study examines gender disparities in scientific misconduct or errors, specifically focusing on differences in retraction rates between male and female first authors in relation to their research productivity. Using a dataset comprising 11,622 retracted articles and 19,475,437 non-retracted articles from the Web of Science and Retraction Watch, we investigate gender differences in retraction rates from the perspectives of retraction reasons, subject fields, and countries. Our findings indicate that male first authors have higher retraction rates, particularly for scientific misconduct such as plagiarism, authorship disputes, ethical issues, duplication, and fabrication/falsification. No significant gender differences were found in retractions attributed to mistakes. Furthermore, male first authors experience significantly higher retraction rates in biomedical and health sciences, as well as in life and earth sciences, whereas female first authors have higher retraction rates in mathematics and computer science. Similar patterns are observed for corresponding authors. Understanding these gendered patterns of retraction may contribute to strategies aimed at reducing their prevalence.

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arXiv2025

Can news and social media attention reduce the influence of problematic research?

News and social media are widely used to disseminate science, but do they also help raise awareness of problems in research? This study investigates whether high levels of news and social media attention might accelerate the retraction process and increase the visibility of retracted articles. To explore this, we analyzed 15,642 news mentions, 6,588 blog mentions, and 404,082 X mentions related to 15,461 retracted articles. Articles receiving high levels of news and X mentions were retracted more quickly than non-mentioned articles in the same broad field and with comparable publication years, author impact, and journal impact. However, this effect was not statistically signicant for articles with high levels of blog mentions. Notably, articles frequently mentioned in the news experienced a significant increase in annual citation rates after their retraction, possibly because media exposure enhances the visibility of retracted articles, making them more likely to be cited. These findings suggest that increased public scrutiny can improve the efficiency of scientific self-correction, although mitigating the influence of retracted articles remains a gradual process.

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arXiv2024

Can social media provide early warning of retraction? Evidence from critical tweets identified by human annotation and large language models

Timely detection of problematic research is essential for safeguarding scientific integrity. To explore whether social media commentary can serve as an early indicator of potentially problematic articles, this study analysed 3,815 tweets referencing 604 retracted articles and 3,373 tweets referencing 668 comparable non-retracted articles. Tweets critical of the articles were identified through both human annotation and large language models (LLMs). Human annotation revealed that 8.3% of retracted articles were associated with at least one critical tweet prior to retraction, compared to only 1.5% of non-retracted articles, highlighting the potential of tweets as early warning signals of retraction. However, critical tweets identified by LLMs (GPT-4o mini, Gemini 2.0 Flash-Lite, and Claude 3.5 Haiku) only partially aligned with human annotation, suggesting that fully automated monitoring of post-publication discourse should be applied with caution. A human-AI collaborative approach may offer a more reliable and scalable alternative, with human expertise helping to filter out tweets critical of issues unrelated to the research integrity of the articles. Overall, this study provides insights into how social media signals, combined with generative AI technologies, may support efforts to strengthen research integrity.

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arXiv2021

A large-scale bibliometric analysis of global climate change research between 2001 and 2018

Global climate change is attracting widespread scientific, political, and public attention owing to the involvement of international initiatives such as the Paris Agreement and the Intergovernmental Panel on Climate Change. We present a large-scale bibliometric analysis based on approximately 120,000 climate change publications between 2001 and 2018 to examine how climate change is studied in scientific research. Our analysis provides an overview of scientific knowledge, shifts of research hotspots, global geographical distribution of research, and focus of individual countries. In our analysis, we identify five key fields in climate change research: physical sciences, paleoclimatology, climate-change ecology, climate technology, and climate policy. We draw the following key conclusions: (1) Over the investigated time period, the focus of climate change research has shifted from understanding the climate system toward climate technologies and policies, such as efficient energy use and legislation. (2) There is an imbalance in scientific production between developed and developing countries. (3) Geography, national demands, and national strategies have been important drivers that influence the research interests and concerns of researchers in different countries. Our study can be used by researchers and policy makers to reflect on the directions in which climate change research is developing and discuss priorities for future research.

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