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We present a case study of how scientometric tools can reveal the structure of scientific theory in a discipline. Specifically, we analyze the patterns of word use in the discipline of cognitive science using latent semantic analysis, a well-known semantic model, in the abstracts of over a thousand academic papers relevant to these theories. Our results show that it is possible to link these theories with specific statistical distributions of words in the abstracts of papers that espouse these theories. We show that theories have different patterns of word use, and that the similarity relationships with each other are intuitive and informative. Moreover, we show that it is possible to predict fairly accurately the theory of a paper by constructing a model of the theories based on their distribution of word use. These results may open new avenues for the application of scientometric tools on theoretical divides.

Phytocompounds and herbal extracts have been utilized in Ayurveda, Siddha and Unani medicine since thousands of years for treatment of various ailments. Success behind herbal medicine strongly suggests the interaction between bio-active phytocompounds with crucial biochemical pathways in a human body without causing adverse effects. The increasing incidence of diseases like cancer instigated the scientific world to focus intently on their pathophysiology and prevention, leading to accelerated research activity in past three decades. This study aims at understanding the evolving global importance of herbal medicine and quality of research against various cancers through scientometric analyses by studying the output from research publications, followed by the contribution from various countries, research institutes, authors, scientific journals and areas of research. To visualize the research structure and dynamics, more than 5000 publications with Science Citation Index that appeared from 1984 to 2013 have been studied and compared for a trend in its growth of publication along with the contributions from various bibliometric parameters stated above. After using the ‘Web of Science’ database it became well evident that the concerned bibliometric parameters contributed substantially in projecting the overall scientific output in the field of herbal anticancer research as reflected from the citation analysis and h-index data. It has been observed that the number of publications increased with compound annual growth rate of 10.39% during the studied periods. Evolving trend of the research topics was visualised by drawing the keyword co-occurrence map in this field.

The number of retracted articles with Chinese authors has raised much attention, but no systematic study has specifically explored the retraction of academic publications by researchers from mainland China. Here, we determined the characteristics of retracted publications from mainland China in the biomedical literature. We searched the Medline database through PubMed and Web of Science to identify retracted publications with first authors from mainland China. Data for 825 retracted studies were included in the analysis. The number and rate of retractions have increased since 1999. We found that 651 retractions were for articles published in journals with relatively low impact factors (< 5). Commonest reasons for retraction were plagiarism (192), errors (159), duplicate publication (143), and invalid peer review (137). Authors of retracted articles were from 28 of the 31 provinces in mainland China. The number of retracted articles from mainland China has shown an increasing trend. Misconduct was the primary reason for retraction. Retracted articles originated from most provinces in China and were published in numerous journals. These findings indicate that misconduct issues are widespread in China. Results of this study highlight the need to take measures to prevent misconduct among Chinese researchers.

AbstractScientific writings, as one essential part of human culture, have evolved over centuries into their current form. Knowing how scientific writings evolved is particularly helpful in understanding how trends in scientific culture developed. It also allows us to better understand how scientific culture was interwoven with human culture generally. The availability of massive digitized texts and the progress in computational technologies today provide us with a convenient and credible way to discern the evolutionary patterns in scientific writings by examining the diachronic linguistic changes. The linguistic changes in scientific writings reflect the genre shifts that took place with historical changes in science and scientific writings. This study investigates a general evolutionary linguistic pattern in scientific writings. It does so by merging two credible computational methods: relative entropy; word-embedding concreteness and imageability. It thus creates a novel quantitative methodology and applies this to the examination of diachronic changes in the Philosophical Transactions of Royal Society (PTRS, 1665–1869). The data from two computational approaches can be well mapped to support the argument that this journal followed the evolutionary trend of increasing professionalization and specialization. But it also shows that language use in this journal was greatly influenced by historical events and other socio-cultural factors. This study, as a “culturomic” approach, demonstrates that the linguistic evolutionary patterns in scientific discourse have been interrupted by external factors even though this scientific discourse would likely have cumulatively developed into a professional and specialized genre. The approaches proposed by this study can make a great contribution to full-text analysis in scientometrics.

International audience; The aim of this article is to test the model analysis conceived by Terry Shinn on the autonomy and unity of science. For him, the differentiation of sciences can be explained in a large part by the diffusion of generic instruments created by research-technologists moving in interstitial arenas between higher education, industry, statistics institutes or the military. We have applied this analysis to research on depression by making the hypothesis that psychiatric rating scales could have played a similar role in the development of this scientific field. To that purpose, we proceeded to a lexicographic study of keywords mentioned in articles listed by the PsycINFO© data base on this subject between 1950 and 2000. In order to realize an associated words analysis, we constructed a co-occurrence matrix and used clustering analysis based on a grouping index; that is, the equivalency index. We obtained significant aggregates of keywords associated with significant periods, or major moments, of the development of research on depression. This periodization confirmed the structural role played by psychiatric rating scales in the development of this scientific field, and led us to discuss and to extend some elements of the model initiated by Shinn.

Being the most proliferative journal of oncology a cancer research of the past decade, the Open Access journal Oncotarget had reached more than 20,000 publications and a relatively high impact factor score in the past years. In 2018, the journal citation report decided to withdraw the status of an impact factor journal. Since there was a large discussion in the scientific community and specific reasons for the withdrawal were not stated, this bibliometric analysis was performed to assess if Oncotarget exhibits any differences in its bibliometric structure compared to other journals. For this purpose, we used the “New Quality and Quantity Indices in Sciences” platform and analyzed 20,000 Oncotarget articles. Density equalizing mapping technique helps to construct maps of cancer research in Oncotarget and shows that it has led to a unique global landscape which is not asymmetrically dominated by the Western hemisphere but exhibits a publishing architecture with a pronounced emphasis on Chinese articles.