J. E. Hirsch
I propose the index $h$, defined as the number of papers with citation number higher or equal to $h$, as a useful index to characterize the scientific output of a researcher.
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I propose the index $\hbar$ ("hbar"), defined as the number of papers of an individual that have citation count larger than or equal to the $\hbar$ of all coauthors of each paper, as a useful index to characterize the scientific output of a researcher that takes into account the effect of multiple coauthorship. The bar is higher for $\hbar$.
We propose a simple way to put in a common scale the h values of researchers working in different scientific ISI fields, so that the previsible misuse of this index for inter-areas comparison might be prevented, or at least, alleviated.
I propose the coefficient, $t_h$, and its modification $N_t$ which in a simple way reflect dynamics of scientific activity of an individual researcher. I determine $t_h$ as a time period (from some moment in the past till the present moment) during which papers responsible for 1/2 of the total citation index were published. Parameter $N_t$ represents average of the citation index over this period: $N_t={\mathrm{C.I.}}/2t_h$.
It has long been known that scientific output proceeds on an exponential increase, or more properly, a logistic growth curve. The interplay between effort and discovery is clear, and the nature of the functional form has been thought to be due to many changes in the scientific process over time. Here I show a quantitative method for examining the ease of scientific progress, another necessary component in understanding scientific discovery. Using examples from three different scientific disciplines - mammalian species, chemical elements, and minor planets - I find the ease of discovery to conf…
The number h of papers with at least h citations has been proposed to evaluate individual's scientific research production. This index is robust in several ways but yet strongly dependent on the research field. We propose a complementary index hI = h^2/N_t, with N_t being the total number of authors in the considered h papers. A researcher with index hI has hI papers with at least hI citation if he/she had published alone. We have obtained the rank plots of h and hI for four Brazilian scientific communities. Contrasting to the h-index curve, the hI index present a perfect data collapse into a …
An index to quantify scientific debt
提出用\(z=\sum\limits_{i=1}^{n} \mathrm{IF}_{i}\)量化科研债务的指数，对比\(h\)指数，指出\(h - z\)能更平衡地评估科学价值。
Rediscovering a new function for something can be just as important as the discovery itself. In 1982, Stephen Jay Gould and Elisabeth Vrba named this phenomenon Exaptation to describe a radical shift in the function of a specific trait during biological evolution. While exaptation is thought to be a fundamental mechanism for generating adaptive innovations, diversity, and sophisticated features, relatively little effort has been made to quantify exaptation outside the topic of biological evolution. We think that this concept provides a useful framework for characterising the emergence of innov…
Are existing ways of measuring scientific quality reflecting disadvantages of not being part of giant collaborations? How could possible discrimination be avoided? We propose indices defined for each discipline (subfield) and which count the plausible contributions added up by collaborators maintaining the spirit of interdependency. Based on the growing debate about defining potential biases and detecting unethical behavior, a standardized method to measure contributions of the astronomical number of coauthors is introduced.
The $K$-index is an easily computable centrality index in complex networks, such as a scientific citations network. A researcher has a $K$-index equal to $K$ if he or she is cited by $K$ articles that have at least $K$ citations. The $K$-index has several advantages over Hirsh's $h$-index and, in previous studies, has shown better correlation with Nobel prizes than any other index given by the {\em Web of Science}, including the $h$-index. It is plausible that researchers who are the most connected to other scientifically well-connected researchers are the most likely to be doing important wor…
An interesting twist of the Hirsch index is given, in terms of an index for topics and compounds. By comparing both the hb index and m for a number of compounds and topics, it can be used to differentiate between a new so-called hot topic with older topics. This quick method is shown to help new comers to identify how much interest and work has already been achieved in their chosen area of research.
h-index has become the most popular indicator for quantifying a scientist's scientific impact in various scientific fields. h-index is defined as the largest number of papers with citation number larger than or equal to h and it treats each citation equally. However, different citations usually come from different papers with different influence and quality, and a citation from a highly influential paper is a greater recognition of the target paper than a citation from an ordinary paper. Based on this assumption, we proposed a new indicator named x-index to quantify a scientist's scientific im…
What do we really mean by a "good" scientific journal? Do we care more about the short-time impact of our papers, or about the chance that they will still be read and cited on the long run? Here I show that, by regarding a journal as a "virtual scientist" that can be attributed a time-dependent Hirsch h-index, we can introduce a parameter that, arguably, better captures the "persistency" of a scientific publication. Curiously, however, this parameter seems to depend above all on the "thickness" of a journal.
We introduce a new centrality index for bipartite network of papers and authors that we call $K$-index. The $K$-index grows with the citation performance of the papers that cite a given researcher and can seen as a measure of scientific social recognition. Indeed, the $K$-index measures the number of hubs, defined in a self-consistent way in the bipartite network, that cites a given author. We show that the $K$-index can be computed by simple inspection of the Web of Science platform and presents several advantages over other centrality indexes, in particular Hirsch $h$-index. The $K$-index is…
The lack of predictability of citation-based measures frequently used to gauge impact, from impact factors to short-term citations, raises a fundamental question: Is there long-term predictability in citation patterns? Here, we derive a mechanistic model for the citation dynamics of individual papers, allowing us to collapse the citation histories of papers from different journals and disciplines into a single curve, indicating that all papers tend to follow the same universal temporal pattern. The observed patterns not only help us uncover basic mechanisms that govern scientific impact but al…
We investigate the problem of counting co-authorhip in order to quantify the impact and relevance of scientific research output through normalized \textit{h-index} and \textit{g-index}. We use the papers whose authors belong to a subset of full professors of the Italian Settore Scientifico Disciplinare (SSD) FIS01 - Experimental Physics. In this SSD two populations, characterized by the number of co-authors of each paper, are roughly present. The total number of citations for each individuals, as well as their h-index and g-index, strongly depends on the average number of co-authors. We show t…
We use an information-theoretic measure of linguistic similarity to investigate the organization and evolution of scientific fields. An analysis of almost 20M papers from the past three decades reveals that the linguistic similarity is related but different from experts and citation-based classifications, leading to an improved view on the organization of science. A temporal analysis of the similarity of fields shows that some fields (e.g., computer science) are becoming increasingly central, but that on average the similarity between pairs has not changed in the last decades. This suggests th…
Quantifying and predicting the long-term impact of scientific writings or individual scholars has important implications for many policy decisions, such as funding proposal evaluation and identifying emerging research fields. In this work, we propose an approach based on Heterogeneous Dynamical Graph Neural Network (HDGNN) to explicitly model and predict the cumulative impact of papers and authors. HDGNN extends heterogeneous GNNs by incorporating temporally evolving characteristics and capturing both structural properties of attributed graph and the growing sequence of citation behavior. HDGN…
Bibliometric measures of individual scientific achievement are of particular interest if they can be used to predict future achievement. Here we report results of an empirical study of the predictive power of the h-index compared to other indicators. Our findings indicate that the h-index is better than other indicators considered (total citation count, citations per paper, and total paper count) in predicting future scientific achievement. We discuss reasons for the superiority of the h-index.
Modern management of research is increasingly based on quantitative bibliometric indices. Nowadays, the h-index is a major measure of research output that has supplanted all other citation-based indices. In this context, indicators that complement the h-index by evaluating different facets of research achievement are compelling. As an additional bibliometric source that can be easily extracted from available databases, we propose to use the number of distinct journals Nj in which an individual's papers were published. We show that Nj is independent of citation counts, and argue that it is a re…
Research Power Ranking: Adapting the Elo System to Quantify Scientist Evaluation
本文提出研究实力排名（RPR）模型，改编Elo系统，通过基础、应用和商业活动三维加权评估科学家，动态反映职业轨迹，为科学声誉评估提供通用工具。
Citation count is a popular index for assessing scientific papers. However, it depends on not only the quality of a paper but also various factors, such as conventionality, team size, and gender. Here, we examine the extent to which the conventionality of a paper is related to its citation percentile in a discipline by using our measure, topic disparity. The topic disparity is the cosine distance between a paper and its discipline on a neural embedding space. Using this measure, we show that the topic disparity is negatively associated with the citation percentile in many disciplines, even aft…
A method based on the classical principal component analysis leads to demonstrate that the role of co-authors should give a h-index measure to a group leader higher than usually accepted. The method rather easily gives what is usually searched for, i.e. an estimate of the role (or "weight") of co-authors, as the additional value to an author papers' popularity. The construction of the co-authorship popularity H-matrix is exemplified and the role of eigenvalues and the main eigenvector component are discussed. An example illustrates the points and serves as the basis for suggesting a generally …
The journal structure in the China Scientific and Technical Papers and Citations Database (CSTPCD) is analysed from three perspectives: the database level, the specialty level and the institutional level (i.e., university journals versus journals issued by the Chinese Academy of Sciences). The results are compared with those for (Chinese) journals included in the Science Citation Index. The frequency of journal-journal citation relations in the CSTPCD is an order of magnitude lower than in the SCI. Chinese journals, especially high-quality journals, prefer to cite international journals rather…
The $α$ person is the dominant person in a group. We define the $α$-author of a paper as the author of the paper with the highest $h$-index among all the coauthors, and an $α$-paper of a scientist as a paper authored or coauthored by the scientist where he/she is the $α$-author. For most but not all papers in the literature there is only one $α$-author. We define the $h_α$ index of a scientist as the number of papers in the $h$-core of the scientist (i.e. the set of papers that contribute to the $h$-index of the scientist) where this scientist is the $α$-author. We also define the $h'_α$ index…
Scientific impact plays a central role in the evaluation of the output of scholars, departments, and institutions. A widely used measure of scientific impact is citations, with a growing body of literature focused on predicting the number of citations obtained by any given publication. The effectiveness of such predictions, however, is fundamentally limited by the power-law distribution of citations, whereby publications with few citations are extremely common and publications with many citations are relatively rare. Given this limitation, in this work we instead address a related question ask…
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 the first empirical verification of the degree to which citation numbers represent scientific impact as it is actually perceived by experts in their respective field. We run a large-scale survey of about 2000 corresponding authors who performed a pairwise impact assessment task across more than 20000 scientific articles. Results of the survey show that citatio…
Science advances by pushing the boundaries of the adjacent possible. While the global scientific enterprise grows at an exponential pace, at the mesoscopic level the exploration and exploitation of research ideas is reflected through the rise and fall of research fields. The empirical literature has largely studied such dynamics on a case-by-case basis, with a focus on explaining how and why communities of knowledge production evolve. Although fields rise and fall on different temporal and population scales, they are generally argued to pass through a common set of evolutionary stages. To unde…
A few new indices to characterize the scientific output of scientists are defined in the paper. These indices are compared with -index and its alternative indices using some proven assertions. The gd-indices are introduced as extensions of the g-index to define H-index as an improvement of the h-index. Numerous computational results which are conducted indicate the good behaviour of defined indices to evaluate the scientific impact of scientists. There exist very good approximations between some pairs of all considered indices in the sense that related ratios are often very close to 1.
There is an overall perception of increased interdisciplinarity in science, but this is difficult to confirm quantitatively owing to the lack of adequate methods to evaluate subjective phenomena. This is no different from the difficulties in establishing quantitative relationships in human and social sciences. In this paper we quantified the interdisciplinarity of scientific journals and science fields by using an entropy measurement based on the diversity of the subject categories of journals citing a specific journal. The methodology consisted in building citation networks using the Journal …
How to measure research performance of single scientists? A proposal for an index based on scientific prizes: The Prize Winner Index (PWI)
本文提出基于合著距离的Prize Winner Index (PWI)来衡量科学家研究绩效，通过计算科学家与著名奖项获奖者的合著距离，验证了PWIPM与P(top 10%)指标具有高相关性，表明其可作为传统文献计量指标的替代方案。
The aggregated journal-journal citation matrix -based on the Journal Citation Reports (JCR) of the Science Citation Index- can be decomposed by indexers and/or algorithmically. In this study, we test the results of two recently available algorithms for the decomposition of large matrices against two content-based classifications of journals: the ISI Subject Categories and the field/subfield classification of Glaenzel & Schubert (2003). The content-based schemes allow for the attribution of more than a single category to a journal, whereas the algorithms maximize the ratio of within-category ci…
One interesting phenomenon that emerges from the typical structure of social networks is the friendship paradox. It states that your friends have on average more friends than you do. Recent efforts have explored variations of it, with numerous implications for the dynamics of social networks. However, the friendship paradox and its variations consider only the topological structure of the networks and neglect many other characteristics that are correlated with node degree. In this article, we take the case of scientific collaborations to investigate whether a similar paradox also arises in ter…
Measuring Scientific Group Performance: Integrating h-Group and Homogeneity into the $α$-Index
本文提出 alpha-index 方法，通过整合团队 h-index 同质性与 h-group 指标来衡量科研团队绩效，并在计算机科学会议评估中验证其与人工分类结果相近。
The h-index is a popular bibliometric indicator for assessing individual scientists. We criticize the h-index from a theoretical point of view. We argue that for the purpose of measuring the overall scientific impact of a scientist (or some other unit of analysis) the h-index behaves in a counterintuitive way. In certain cases, the mechanism used by the h-index to aggregate publication and citation statistics into a single number leads to inconsistencies in the way in which scientists are ranked. Our conclusion is that the h-index cannot be considered an appropriate indicator of a scientist's …
Quantifying the Benefit of Artificial Intelligence for Scientific Research
本研究开发了测量框架，通过分析7460万篇文献和710万项专利，揭示了AI在科学研究中广泛使用且带来引用优势，同时指出AI教育与应用脱节及人口统计学不平等问题。
We provide a comprehensive and critical review of the h-index and its most important modifications proposed in the literature, as well as of other similar indicators measuring research output and impact. Extensions of some of these indices are presented and illustrated.
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 index CITEX, which gives normalized scores to authors and papers to determine their rankings. To the best of our knowledge, this is the first citation index which simultaneously assigns scores to both authors and papers. Using these scores, we can get an objective measure of the reputation of an author and the impact of a paper. We model this problem as an …
The citation distribution of a researcher shows the impact of their production and determines the success of their scientific career. However, its application in scientific evaluation is difficult due to the bi-dimensional character of the distribution. Some bibliometric indexes that try to synthesize in a numerical value the principal characteristics of this distribution have been proposed recently. In contrast with other bibliometric measures, the biases that the distribution tails provoke, are reduced by the h-index. However, some limitations in the discrimination among researchers with dif…
Large scientific teams are more, not less, disruptive
本研究通过分析约6000万篇论文，指出小团队颠覆性优势是测量假象，提出参考稳健度量，证明大型团队更具颠覆性。
For decades the number of scientific publications has been rapidly increasing, effectively out-dating knowledge at a tremendous rate. Only few scientific milestones remain relevant and continuously attract citations. Here we quantify how long scientific work remains being utilized, how long it takes before today's work is forgotten, and how milestone papers differ from those forgotten. To answer these questions, we study the complete temporal citation network of all American Physical Society journals. We quantify the probability of attracting citations for individual publications based on age …
In addition to science citation indicators of journals like impact and immediacy, social network analysis provides a set of centrality measures like degree, betweenness, and closeness centrality. These measures are first analyzed for the entire set of 7,379 journals included in the Journal Citation Reports of the Science Citation Index and the Social Sciences Citation Index 2004, and then also in relation to local citation environments which can be considered as proxies of specialties and disciplines. Betweenness centrality is shown to be an indicator of the interdisciplinarity of journals, bu…
Modern society is increasingly massively connected, reflecting an omnipresent tendency to organize social, economic, and technological structures in complex networks. Recently, with the advent of the so-called multiplex networks, new concepts and tools were necessary to better understand the characteristics of this type of system, as well as to analyze and quantify its performance and efficiency. The concept of diversity in multiplex networks is a striking example of this intrinsically interdisciplinary efort to better understand the nature of complex networks. In this work, we introduce the M…
The Hirsch's $h$-index is perhaps the most popular citation-based measure of the scientific excellence. In 2013 G. Ionescu and B. Chopard proposed an agent-based model for this index to describe a publications and citations generation process in an abstract scientific community. With such an approach one can simulate a single scientist's activity, and by extension investigate the whole community of researchers. Even though this approach predicts quite well the $h$-index from bibliometric data, only a solution based on simulations was given. In this paper, we complete their results with exact, …
We present a general Bayesian method for quantifying the statistical reliability of one-dimensional measures of scientific quality based on citation data. Two quality measures used in practice -- ``papers per year'' and ``Hirsch's $h$'' -- are shown to lack the accuracy and precision necessary to be useful. The mean, median and maximum number of citations are on the other hand reliable and permit accurate predictions of future author performance on the basis of as few as 50 publications.
I propose to sharpen the index h, proposed by Hirsch as a useful index to characterize the scientific output of a researcher, by excluding the self-citations. Performing a self-experiment and also analyzing two anonymous data sets, it is shown that self-citations can significantly reduce the $h$ index in contrast to Hirsch's expectations. This result is confirmed by an analysis of 13 further data sets.
Aggregated journal-journal citation networks based on the Journal Citation Reports 2004 of the Science Citation Index (5968 journals) and the Social Science Citation Index (1712 journals) are made accessible from the perspective of any of these journals. The user is thus able to analyze the citation environment in terms of links and graphs. Furthermore, the local impact of a journal is defined as its share of the total citations in the specific journal's citation environments; the vertical size of the nodes is varied proportionally to this citation impact. The horizontal size of each node can …
In the book The Essential Tension Thomas Kuhn described the conflict between tradition and innovation in scientific research --i.e., the desire to explore new promising areas, counterposed to the need to capitalize on the work done in the past. While it is true that along their careers many scientists probably felt this tension, only few works have tried to quantify it. Here, we address this question by analyzing a large-scale dataset, containing all the papers published by the American Physical Society (APS) in more than $25$ years, which allows for a better understanding of scientists' caree…
The number of citations is a widely used metric to evaluate the scientific credit of papers, scientists and journals. However, it does happen that a paper with fewer citations from prestigious scientists is of higher influence than papers with more citations. In this paper, we argue that from whom the paper is being cited is of higher significance than merely the number of received citations. Accordingly, we propose an interactive model on author-paper bipartite networks as well as an iterative algorithm to get better rankings for scientists and their publications. The main advantage of this m…
Scientists are embedded in social and information networks that influence and are influenced by the quality of their scientific work, its impact, and the recognition they receive. Here we quantify the systematic relationship between a scientist's position in the network of scientific collaborations and the citations they receive. As expected, we find that authors closer to others in this network are, on average, more highly cited than those further away from others. We construct a novel indicator, the s-index, that explicitly captures performance linked to network position along two compliment…
Despite the apparent cross-disciplinary interactions among scientific fields, a formal description of their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time e…
The survival of scientific stylization
论文提出基于文本的指标衡量风格化科学研究，发现其虽具持续颠覆性却面临引用偏低和评审周期延长的衰退，呼吁改革同行评审与影响力评价机制。
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