Finding citations for PubMed: a large-scale comparison between five freely available bibliographic data sources

uCite: The union of nine large-scale public PubMed citation datasets with reliability filtering

There has been a recent push to make public, aggregate, and increase coverage of bibliographic citation data. Here we describe uCite, a citation dataset containing 564 million PubMed citation pairs aggregated from the following nine sources: PubMed Central, iCite, OpenCitations, Dimensions, Microsoft Academic Graph, Aminer, Semantic Scholar, Lens, and OpCitance. Of these, 51 million (9%) were labeled unreliable, as determined by patterns of source discrepancies explained by ambiguous metadata, crosswalk, and typographical errors, citing future publications, and multi-paper documents. Each source contributes to improved coverage and reliability, but varies dramatically in precision and recall, estimates of which are contrasted with the Web of Science and Scopus herein.

Bridging the gap in author names: building an enhanced author name dataset for biomedical literature system

OBJECTIVE

Author name incompleteness, referring to only first initial available instead of full first name, is a long-standing problem in MEDLINE and has a negative impact on biomedical literature systems. The purpose of this study is to create an Enhanced Author Names (EAN) dataset for MEDLINE that maximizes the number of complete author names.

MATERIALS AND METHODS

The EAN dataset is built based on a large-scale name comparison and restoration with author names collected from multiple literature databases such as MEDLINE, Microsoft Academic Graph, and Semantic Scholar. We assess the impact of EAN on biomedical literature systems by conducting comparative and statistical analyses between EAN and MEDLINE's author names dataset (MAN) on 2 important tasks, author name search and author name disambiguation.

RESULTS

Evaluation results show that EAN improves the number of full author names in MEDLINE from 69.73 million to 110.9 million. EAN not only restores a substantial number of abbreviated names prior to the year 2002 when the NLM changed its author name indexing policy but also improves the availability of full author names in articles published afterward. The evaluation of the author name search and author name disambiguation tasks reveal that EAN is able to significantly enhance both tasks compared to MAN.

CONCLUSION

The extensive coverage of full names in EAN suggests that the name incompleteness issue can be largely mitigated. This has significant implications for the development of an improved biomedical literature system. EAN is available at https://zenodo.org/record/10251358, and an updated version is available at https://zenodo.org/records/10663234.

A construction and empirical research of the journal disruption index based on open citation data

For many years, the journal evaluation system has been centered on impact indicators, resulting in evaluation results that do not reflect the academic innovation of journals. To solve this issue, this study attempts to construct the Journal Disruption Index (JDI) from the perspective of measuring the disruption of each journal article. In the actual study, we measured the disruption of articles of 22 selected virology journals based on the OpenCitations Index of Crossref open DOI-to-DOI citations (COCI) first. Then we calculated the JDI of 22 virology journals based on the absolute disruption index (D Z ) of the articles. Finally, we conducted an empirical study on the differences and correlations between the impact indicators and disruption indicators as well as the evaluation effect of the disruption index. The results of the study show: (1) There are large differences in the ranking of journals based on disruption indicators and impact indicators. Among the 22 journals, 12 are ranked higher by JDI than Cumulative Impact Factor for 5 years (CIF5), the Journal Index for PR6 (JIPR6) and average Percentile in Subject Area (aPSA). The ranking difference of 17 journals between the two kinds of indicators is greater than or equal to 5. (2) There is a medium correlation between disruption indicators and impact indicators at the level of journals and papers. JDI is moderately correlated with CIF5, JIPR6 and aPSA, with correlation coefficients of 0.486, 0.471 and - 0.448, respectively. D Z was also moderately correlated with Cumulative Citation (CC), Percentile Ranking with 6 Classifications (PR6) and Percentile in Subject Area (PSA) with correlation coefficients of 0.593, 0.575 and - 0.593, respectively. (3) Compared with traditional impact indicators, the results of journal disruption evaluation are more consistent with the evaluation results of experts' peer review. JDI reflects the innovation level of journals to a certain extent, which is helpful to promote the evaluation of innovation in sci-tech journals.

Bibliometric Analysis of Poor Oral Health as a Risk Factor for Oral Cancer

Poor oral health is a risk factor for oral cancer, and bibliometrics can tell us important things about publication trends and research. Oral cancer risk factors include smoking, betel nut chewing, alcohol consumption, trauma from sharp teeth, chronic infections, and other factors related to oral health. There is a need to understand the role of poor oral health as a risk factor. Thus, this study aimed to conduct a bibliometric analysis of the literature on poor oral health as a risk factor for oral cancer. A bibliometric analysis was conducted for poor oral health as a risk factor for oral cancer using RStudio 2021.09.0+351 "Ghost Orchid" Release (2021-09-20) for Windows, package "bibliometrix." The literary data for this study were derived from Elsevier's Scopus database, and the data were exported in BibTex format. The results considered the time frame of 1983 to 2022, with journals, books, newspaper articles, and others as sources, accounting for a total of 543 documents. The search yielded a total of 2,882 authors, with a total of 3,306 appearances. The results show that the research on poor oral health and oral cancer is mainly led by the United States (106), India (49), and China (46). The top author is Warnakulasuriya S, followed by Worthington HV. The research shows the countries that are currently working on the topics and helps set up future collaborations to improve the evidence produced and help the scientific community by finding research gaps and experts in this area of research.