Scientometrics最新文献

Besides the highest academic degree with lots of merits post that, getting a Ph.D. and the journey throughout the Ph.D. is not so easy due to which stress and trauma become common among Ph.D. research students. Stress among them can’t be overlooked and is also of major concern as it not only impacts their academic performances but also their mental health, and increases emotional exhaustion. There are many factors that are involved in causing stress among students. Doctoral students are more prone to it as it demands time, selfless effort, and much sacrifice. Moreover, they are in the stage where there are a lot of things going on that distract their minds or sometimes contradict their decisions be it related to their future or to their family, or be it from the institute side. This article mainly deals with analyzing the factors which cause stress, their effects on Ph.D. students, how these factors interrelate with each other, and their percentage share in causing this. Seven dimensions/factors are explored i.e., Institutional Issues, Personal Issues, Supervisor relations, Academic Issues, Fears, Mental Health, and Time Management, which overall depict the entire Doctoral journey. For the analysis of all these dimensions and for finding out the percentage share, a new hybrid method of MCDA (Multi-Criteria Decision Analysis) i.e., fuzzy DEMATEL-ANP with the triangular approach of responses i.e., Optimistic, Pessimistic & Most-Likely is proposed. Performance Analysis and Sensitivity Analysis are done to do the validity check and robustness of the proposed model and by doing this analysis, we identified that the most likely approach in the proposed model is most reliable than the Optimistic and Pessimistic approach due to its non-biased behavior and Supervisor feedback and Uncertain future are the most influential factors and change of city is the least influential one. Moreover, Academic Issues (Poor Writing Skills as well as Publication issues) together with Satisfaction with topic selection during course work period as well as the supervisor's feedback contributes more with weights of 8.1%, 7.7% & 7.5% respectively in causing stress to the doctoral students.

Based on the extracted information of retracted papers from the Retraction Watch Database and the citation information of these papers from the Web of Science, we uncovered the complex relationships of retracted papers in the molecular biology domain via a citation network. The basic characteristics (i.e., time and spatial patterns, reasons, publishers) of the retracted articles were studied. Citation network analysis, including community detection and text analysis, was carried out. Our main findings are as follows: (1) The overall number of retractions in this field has been increasing over time, and these retractions have been mainly in China and the USA. (2) Most retracted papers were for both “scientific error” and “misconduct” reasons. Among the 13 reasons given, errors in the data and images accounted for the largest proportion. (3) Community structure is obvious in the citation network we constructed. In communities with five or more nodes, the average self-citation rate account for 76%. In the three largest communities 1, 2, and 3, the self-citation rate are respectively 99%, 100% and 77%. In community 6, the self-catition rate is 17%. Other papers from different teams were published in the Journal of Cellular Biochemistry (4 papers). Tumor Biology (3 papers) or Febs Letters (1 paper). The self-citation rate of community 5 is 60.00%. Most papers are from Alfredo Fusco’s team, and other ten papers are almost published in PLoS ONE. (4) The coupling relationship between citing-cited retraction reasons was revealed. Retractions and their citations were more likely to be retracted for the same reason. Most of the citing-cited papers from paper mills were published by the same publisher and even the same journal. (5) PI3K (an enzyme), WNT (a protein) and lncRNAs have recently been the major topics of retractions.

Interdisciplinarity is a polysemous concept with multiple, reasoned and intuitive, interpretations across scholars and policy-makers. Historically, quantifying the interdisciplinarity of research has been challenging due to the variety of methods used to identify metadata, taxonomies, and mathematical formulas. This has resulted in considerable uncertainty about the ability of quantitative models to provide clear insights for policy-making. This study proposes a systemic design, grounded in an advanced literature review, to demonstrate that the quantification of the interdisciplinarity of research can be treated as a process of decision-making in mathematical modelling, where alternatives choices are evaluated based on how closely their mathematical properties align with the theoretical objectives of the research design. The study addresses modeling choices regarding the stylisation of metadata into units of observation, and the operational definition of the conceptual dimensions of interdisciplinarity, presenting both established and novel methods and formulas. The final section discusses advanced topics in modelling the measurement, including a dedicated discussion on the difference in analysing the status of papers versus collective bodies of research; and distinguishing between reflective, formative, and inferential causal models of interdisciplinary research.

Academic evaluation is a critical component of research, with the interaction between quantitative and qualitative assessments becoming a prominent area of focus. This study examines the relationship between peer review scores and citations within the framework of open peer review. Utilizing data from the OpenReview platform for papers presented at the International Conference on Learning Representations (ICLR), the papers were classified into oral presentations, poster presentations, and rejected manuscripts. Weighted scores were calculated using the confidence score method, followed by an analysis using correlation and regression techniques. The findings reveal significant differences among the three categories in terms of review scores and citations, demonstrating a positive correlation between review scores and citations. Additionally, it was found that papers with greater inconsistency in reviews tended to receive higher citations. Reviewers of rejected papers displayed significantly higher confidence in their assessments compared to reviewers of accepted papers. The results highlight the alignment between peer review and traditional bibliometric indicators in the context of open peer review. However, the degree of concordance between the two evaluation methods is not substantial, suggesting that they are not interchangeable. Therefore, traditional bibliometric indicators should be considered an essential complement to peer review. Furthermore, when evaluating the consistency between quantitative and qualitative assessments and the confidence levels of reviewers, peer review demonstrates greater effectiveness than “traditional peer review” in addressing issues of “poor selection”.

Understanding citations within their context is a complex task in information science, critical for bibliometric analysis. The study of citation contexts and their types has been a central issue in recent work on citations. In this paper, we present an experiment on the semantic annotation of citation contexts using a rule-based approach. We processed articles from seven PLOS journals and performed semantic annotation of citation contexts based on linguistic resources we constructed. We built on previous work on verb form analysis, n-grams, and semantic category modeling in the form of a linguistic ontology. Based on our observations, we propose directions of work for the constitution of a semantically annotated corpora. The intermediate results obtained lead us to formulate hypotheses on the relation between the IMRaD structure and certain semantic categories. Furthermore, our results demonstrate the semantic richness of citation contexts and underscore the importance of access to full-text articles for ontology population in open science. The findings suggest that semantic categories vary across disciplines and rhetorical structures, necessitating further exploration with larger and more diverse datasets.

Comprehending the patterns of knowledge evolution benefits funding agencies, policymakers, and researchers in developing creative ideas. We introduce the notation of scientific knowledge role transition as an evolution from informal to formal. We investigate how different factors affect the role transition of scientific knowledge, considering the two primary levels—transition pace and transition possibility. The interpretive machine learning models are conducted to discover that the Gradient Boosting classifier performs better for predicting transition possibility, and Random Forests regression is the most effective for predicting transition pace. Specifically, knowledge attribute features have a more obvious effect on the transition probability, while knowledge network structure has a greater effect on the transition pace. We further find that knowledge relatedness and citation number have negative effects on knowledge role transition, while adoption frequency, indegree centrality in the knowledge citation network, node number of the egocentric co-occurrence network, and journal impact of scientific knowledge have positive effects. The aforementioned discoveries enhance our comprehension of scientific knowledge evolution patterns and provide insight into the trajectory of scientific and technological advancement.

Open Access (OA) publication often entails payment of Article processing charges (APCs), particularly in the so-called Hybrid and Gold journals. The growth of Gold OA publications linked to the development of OA mandates has forced funders, research institutions, and researchers to develop strategies to pay APCs. Thus, this research tries to estimate the percentage of the budget of the projects funded by the Spanish State Plan for the Generation of Knowledge and Scientific and Technological Strengthening of the R&D&I, Spain's two main public project funding calls in Spain. The period studied is 2013–2019. Additionally, we study the relationships between publication intensity, funding attraction, and the availability of OA journals with APC expenditure at the area level. The results show that €45.87 million were spent on APCs, with most projects spending 3–8% of their budgets. However, numerous outliers with rates over 10% suggest further study on the role of APCs in the financial performance of the research activity. Estimations shown in the paper have to be taken cautiously as the APCs of the publications related to the projects studied in this analysis might not have been fully paid with the projects’ budget but using other funding strategies. Further research is needed to address the researchers’ decisions better when paying APCs. Finally, publication intensity, funding attraction, and the availability of OA journals are highly correlated with the investment in APCs in different fields. These results show that the current APC framework affects disciplines differently and raises questions about alternative publishing and funding models.

This study outlines the intellectual structure of Library and Information Science in terms of the venues with RefCit2vec, an embedding method inspired by word2vec. The reference lists or cited-by lists of 62,077 articles in 35 venues (journals and proceedings) between 1928 and 2022 are converted into real number vectors by four independent models of RefCit2vec. The document similarities measured by the two models of RefCit2vec exhibit moderate correlations with bibliographical coupling metrics. In contrast, the similarities from the other two models moderately or strongly correlate with co-citation metrics. Each venue is represented by its centroid, the average vector of its constituent documents. By applying hierarchical agglomerative clustering on the venue centroids, 69% of venues robustly emerge in 6 out of 8 clusters. Four clusters consistently form the library-related branch. The bibliometrics/scientometrics branch contains only 1 cluster, whereas the information-related branch contains 3 clusters. 43% of venues are in six subgroups of consistent tree structures. An article is defined as SCIM-alike for it is closer to the SCIM centroid than half of SCIM articles are. 10% of JASIST articles are SCIM-alike upon their reference lists, and 5% of JASIST articles are SCIM-alike in terms of their cited-by lists. The percentage of SCIM-alike articles in JASIST hiked above the average between 2008 and 2018 but has dropped below the average since 2019. As we demonstrate the dynamics in LIS, citation embedding methods like RefCit2vec can incorporate citation-based, text-based, or authorship features to contribute to varied scenarios in investigating or exploring research fronts and scientific knowledge transfer.

In recent years, there has been a growing interest in the measurement of research performance. These studies evaluate a country or groups of countries according to their research performance and make some inferences to improve their performance. This study analyses the research performance of Turkish higher education, which aims for higher positions in international rankings, in the context of publication productivity, impact and collaboration with data based on Web of Science and comprehensive indicators for the years 1980–2022. In addition, research area-based analyses were also made. In this way, by presenting Türkiye’s performance from past to present in a comprehensive manner, rich information has been provided to policy makers, decision makers, and practical implications have been made for the improvement of performance. According to the results of the study, Türkiye has been faced with low productivity for many years. Both the area-based analyses and the results for the overall publication impact revealed that although there has been an increase in publication impact in recent years, Türkiye’s publication impact has performed below the world average in all years examined. The results indicated that Turkish higher education has some problems in terms of quality. As for research collaboration, the results showed that Türkiye gives more importance to domestic collaborative publications rather than international collaboration, while industry collaboration continues to remain in the background. Based on the results of the study, practical implications for policy makers and decision makers were made.

This study investigates the factors influencing surname initial techniques in academic publications and their impact on citation counts. Focusing on the disciplines of Economics, Psychology, Political Science, and Sociology, we utilized data from the top 500 universities listed in the Shanghai List. Examining 70.377 academic publications from 2.278 academics published between 2011 and 2020, the study reveals that alphabetical ordering is more prevalent in Economics and Political Science. Academics with surnames placed at the beginning of the alphabet in these fields experience increased visibility and recognition. Conversely, those with surnames placed at the end of the alphabet face disadvantages and often employ strategies such as changing surname initials, using hyphenated surnames, or adding prefixes to improve their positioning in the author list of the article. These strategies, influenced by factors like the number of authors, country of origin, gender and whether the advantage is gained or not in positioning of author list, help mitigate the unfairness caused by alphabetization and positively contribute to authors’ citation statistics.