Historically Black Colleges and Universities (HBCUs) play a foundational role in promoting equality in U.S. higher education and society. Studying faculty transitions and research dynamics at HBCUs is crucial to understanding and addressing these institutions’ challenges, such as the brain drain and its relationships with faculty research practices. By tracking the affiliation changes of 139 professors and their research outcomes (consisting of 4,269 publications) and comparing them with a matched control group with similar backgrounds, we revealed a moving penalty for professors moving from Predominantly White Institutions (PWIs) to HBCUs, who experienced declines in research productivity and citation impact. In contrast, professors transitioning from HBCUs to PWIs benefited from the moving premium of increasing high-impact publications. Professors at HBCUs tend to increase their collaborations with PWIs before transitioning, while those moving to PWIs reduce their collaborations with HBCUs. Our findings highlight the ongoing challenges HBCUs face and underscore the need for comprehensive strategies to strengthen these institutions’ research functionality and ultimately their overall academic standing.

As an essential mechanism of scientific self-correction, articles are retracted for many reasons, including errors in processing data and computation of results. In today’s data-driven science, the validity of research data and results significantly depends on the software employed. We investigate the relationship between software usage and research validity, eventually leading to article retraction, by analyzing software mentioned across 1,924 retraction notices and 3,271 retracted articles. We systematically compare software mentions and related information with control articles sampled by coarsened exact matching by recognizing publication year, scientific domain, and journal rank. We identify article retractions caused by software errors or misuse and find that retracted articles use less free and open-source software, hampering reproducible research and quality control. Moreover, such differences are also present concerning software citation, where retracted articles less frequently follow software citation guidelines regarding free and open-source software.

This study investigates China’s international research collaboration with the United States through a bibliometric analysis of coauthorship over time using historical research publication data. We investigate from three perspectives: overall, high-impact, and high-technology research collaborations using data from Web of Science (WoS), Nature Index , and Technology Alert List maintained by the U.S. Department of State. The results show that the United States is China’s largest research collaborator and that in all three aspects, China and the United States are each other’s primary collaborators much of the time. From China’s perspective, we have found weakening collaboration with the United States over the past 2 years. In terms of high-impact research collaboration, China has historically shared a higher percentage of its research with the United States than vice versa. In terms of high-technology research, the situation is reversed, with the United States sharing more. The percentage of the United States’ high-technology research shared with China has been continuously increasing over the past 10 years, while in China the percentage has been relatively stable.

Citation sentiment plays an important role in citation analysis and scholarly communication research, but prior citation sentiment studies have used small data sets and relied largely on manual annotation. This paper uses a large data set of PubMed Central (PMC) full-text publications and analyzes citation sentiment in more than 32 million citances within PMC, revealing citation sentiment patterns at the journal and discipline levels. This paper finds a weak relationship between a journal’s citation impact (as measured by CiteScore) and the average sentiment score of citances to its publications. When journals are aggregated into quartiles based on citation impact, we find that journals in higher quartiles are cited more favorably than those in the lower quartiles. Further, social science journals are found to be cited with higher sentiment, followed by engineering and natural science and biomedical journals, respectively. This result may be attributed to disciplinary discourse patterns in which social science researchers tend to use more subjective terms to describe others’ work than do natural science or biomedical researchers.