相关论文: The validation of (advanced) bibliometric indicato…
The scientific community increasingly relies on open data sharing, yet existing metrics inadequately capture the true impact of datasets as research outputs. Traditional measures, such as the h-index, focus on publications and citations but…
Measuring the impact of a publication in a fair way is a significant challenge in bibliometrics, as it must not introduce biases between fields and should enable comparison of the impact of publications from different years. In this paper,…
In this paper, we show that citation counts work better than a random baseline (by a margin of 10%) in distinguishing excellent research, while Mendeley reader counts don't work better than the baseline. Specifically, we study the potential…
A number of journal classification systems have been developed in bibliometrics since the launch of the Citation Indices by the Institute of Scientific Information (ISI) in the 1960s. These systems are used to normalize citation counts with…
Bibliometric indicators, citation counts and/or download counts are increasingly being used to inform personnel decisions such as hiring or promotions. These statistics are very often misused. Here we provide a guide to the factors which…
Effective scientific communication depends on accurate citations that validate sources and guide readers to supporting evidence. Yet academic literature faces mounting challenges: semantic citation errors that misrepresent sources,…
Evaluating the performance of researchers and measuring the impact of papers written by scientists is the main objective of citation analysis. Various indices and metrics have been proposed for this. In this paper, we propose a new citation…
This paper proposes an indicator of journals' scientific prestige, the SJR indicator, for ranking scholarly journals based on citation weighting schemes and eigenvector centrality to be used in complex and heterogeneous citation networks…
Citations are commonly held to represent scientific impact. To date, however, there is no empirical evidence in support of this postulate that is central to research assessment exercises and Science of Science studies. Here, we report on…
In recent years, several Scientometrics and Bibliometrics indicators were proposed to evaluate the scientific impact of individuals, institutions, colleges, universities and research teams. The h-index gives a major breakthrough in the…
The concept of h-index has been proposed to easily assess a researcher's performance with a single number. However, by using only this number, we lose significant information about the distribution of citations per article in an author's…
Bibliometric indicators are increasingly used in support of decisions for recruitment, career advancement, rewarding and selective funding for scientists. Given the importance of the applications, bibliometricians are obligated to carry out…
Recently, Wu, Wang, and Evans (2019) and Bu, Waltman, and Huang (2019) proposed a new family of indicators, which measure whether a scientific publication is disruptive to a field or tradition of research. Such disruptive influences are…
Altmetrics are web-based quantitative impact or attention indicators for academic articles that have been proposed to supplement citation counts. This article reports the first assessment of the extent to which mature altmetrics from…
For more than 40 years, the Institute for Scientific Information (ISI, now part of Thomson Reuters) produced the only available bibliographic databases from which bibliometricians could compile large-scale bibliometric indicators. ISI's…
Quantifying the interdisciplinarity of a research is a relevant problem in the evaluative bibliometrics. The concept of interdisciplinarity is ambiguous and multidimensional. Thus, different measures of interdisciplinarity have been propose…
Many other factors affecting citation of publications, except for research area coverage, have been studied. This study aims to investigate impact of research area coverage. Bibliometric papers and their related papers (referred papers,…
Large language models (LLMs) often produce unsupported or unverifiable content, known as "hallucinations." To mitigate this, retrieval-augmented LLMs incorporate citations, grounding the content in verifiable sources. Despite such…
The deluge of new papers has significantly blocked the development of academics, which is mainly caused by author-level and publication-level evaluation metrics that only focus on quantity. Those metrics have resulted in several severe…
This paper presents a bibliometric analysis that examines the works cited in, as well as those citing, NIME papers; for brevity, we refer to these as `references` and `citations`. Utilizing existing tools, we have computationally extracted…