The diffusion of H-related literature
Highlights
► We traced the diffusion of h-related literature over a five-year period beginning with the introduction of the h-index. ► A reliable and representative publication set of h-related literatures has been retrieved. ► A hybrid clustering analysis of h-related literatures was conducted and resulted in four clusters representing different aspects of basic and applied research. ► Topic- and method-related applications of h-index outside the field are discussed.
Introduction
When Jorge Hirsch proposed his new “index to quantify an individual's scientific input” in 2005 (Hirsch, 2005), he did probably not even guess that he had launched a new research direction in informetrics and scientometrics. Discussion of the h-index, its properties, advantages and disadvantages as well as possible improvements and fields of application was started up by the research community still in 2005 and the beginning of 2006. In particular, the new index has immediately found interest in the public (Anon, 2005, Ball, 2005, Peterson, 2005, Roediger, 2006), and received positive reception both in the physics community (Diniz Batista et al., 2005, Popov, 2005; Dume, 2006) and the scientometrics literature (Bornmann and Daniel, 2005, Braun et al., 2005, Glänzel, 2006a, Glänzel, 2006b). Later a series of h-related publications addressed to a broader audience appeared in Nature (Ball, 2007, Ball, 2008, Kelly and Jennions, 2007, Wendl, 2007) and Science (Carbon, 2010, Jones et al., 2008, Sekercioglu, 2008). The h-index has become so popular that it is included as one of the standard indicators in Thomson Reuters’ Web of Science and Elsevier's Scopus less than two years after its formulation. According to the related data of publications and citations (see the data section) h-index is still an increasingly hot topic nowadays.
The h-index originally proposed by a physicist has been extensively studied by scientists with background in almost all fields of the sciences, social sciences and humanities. A plethora of studies was devoted to the analysis of the h-index regarding both theoretical and empirical aspects. On the theoretical side, new variants and derivatives of the h-index have been introduced to improve the original h-index and overcome some of its drawbacks (for instance, Bornmann and Daniel, 2009, Bornmann and Daniel, 2010, Cabrerizo et al., 2010, Vinkler, 2009, Zhang, 2009). Among others, the g-index (Egghe, 2006) and the A-index (Jin, Liang, & Rousseau, 2007) succeeded in attaining a great interests from the scientific community.
Some axiomatic and mathematical interpretations, as well as some models of the h-type indices have been widely addressed (Burrell, 2007, Egghe and Rousseau, 2006, Egghe, 2008a, Egghe, 2009a, Glänzel, 2006a, Glänzel, 2006b, Glänzel, 2010, Schubert, 2007, Tol, 2009, Vanclay, 2007, Woeginger, 2008a, Woeginger, 2008b, Ye, 2009). Egghe (2009b) studied mathematical properties of h-index sequences as developed by Liang (2006). In Glänzel and Schubert (2010), a generalisation of the h-index and g-index was given on the basis of nonnegative real-valued functionals defined on subspaces of the vector space generated by the ordered samples. The authors further defined several Hirsch-type measures and analysed their basic properties.
Several particular problems related to possible biases of the h-index have been discussed as well. For instance, the question of how self-citations may affect the h-index (Brown, 2009, Engqvist and Frommen, 2008, Engqvist and Frommen, 2010, Gianoli and Molina-Montenegro, 2009, Schreiber, 2007a, Schreiber, 2008a, Zhivotovsky and Krutovsky, 2008) and of how to deal with the multi-authorship in finding a ‘fair’ version of the h-index (Egghe, 2008b, Leimu et al., 2008, Hu et al., 2010, Schreiber, 2008b, Schreiber, 2008c, Schreiber, 2009). The calculation of the h-index based on different databases: ISI Web of Science, Scopus and Google Scholar (Bar-Ilan, 2008, Jacsó, 2008, Meho and Rogers, 2008, Meho and Yang, 2007).
Beyond the theoretical discussions, Hirsch-type measures have invoked a large application related literature as well. Following Hirsch's original idea, scientists directly used h-index to measure and compare the research performance of individual researchers: for instance, Cronin and Meho (2006) and Oppenheim (2007) used the h-index to rank prominent informetricians; Bornmann and Daniel (2005) evaluated post-doctor research fellowships applicants based on their h-indices. In contrast to Hirsch's original idea to use his measure for the evaluation of the elite, Schreiber (2007b) conducted a case study of the h-index for 26 non-prominent physicists and Opthof and Wilde (2009) explored the h-index together with bibliometric parameters for the assessment of the scientific output of 29 Dutch professors in clinical cardiology.
Although the h-index was originally designed for the assessment of the performance of individual researchers, its application has very soon been extended to the meso level. Several authors have used h-type indices for quantifying the scientific output of research groups and institutes (e.g., Arencibia-Jorge et al., 2008, Egghe and Rao, 2008, Gorraiz et al., 2009, Grant et al., 2007, Molinari and Molinari, 2008). van Raan (2006) related the h-index of 147 different chemistry research groups to other bibliometric indicators and with peer judgement. Further examples are Mugnaini, Packer, & Meneghini (2008), who presented a comparison based on the h-index between the Brazilian Academy of Sciences and the National Academy of Sciences of the USA; Molinari and Molinari (2008) proposed a new approach for comparing the scientific productivity and visibility of institutions inspired by h-index and Mingers (2009) applied the h-index to three groups of management academics “to evaluate the extent to which the h-index would serve as a reliable measure of the contribution of researchers in the management field”.
Similarly to the already mentioned paper by van Raan (2006), several studies were dedicated to the analysis of the relationship between the h-index and traditional citation-based bibliometric indicators at different levels of aggregation. Costas and Bordons (2007) used the publication data of scientists working at CSIC in Natural Resources to analyse the correlation between the h-index and other bibliometric indicators. The authors (Costas & Bordons, 2008) further compared the h-index and the g-index, and found that g-index is more sensitive than h-index in the assessment of selective scientists. Bornmann, Mutz, & Daniel, 2008 examined empirical results on the h-index and its most important derivatives to determine whether these variants are associated with an incremental contribution for evaluation purposes.
Braun et al., 2005, Braun et al., 2006 proposed the application of the h-index to the evaluation of journals impact which is considered to be a robust supplement to the ISI Impact Factor and related journal citation measures. Inspired by this idea, many studies have applied for evaluating or ranking journals (Bar-Ilan, 2010, Harzing and van der Wal, 2009, Hua et al., 2009, Moed, 2010, Moussa and Touzani, 2010, Ritzberger, 2008, Yu et al., 2009a, Yu et al., 2009b). Some authors then transplanted the method to assess the scientific impact of science conferences (Martins et al., 2010, Souto et al, 2007). Banks (2006) went a step farther by defining the h-index for topics and compounds. Another interesting generalisation was given by Guan and Gao (2009), who explored the applicability of the h-index in the context of patents in technometrics.
Finally some applications of h-index have been made at the macro level as well; for instance, Csajbok, Berhidi, and Vasas (2007) and Jacsó (2009) used the index to measure scientific performance in different countries.
Although the mainstream research on the h-index and related measures was conducted in the field of informetrics and scientometrics, the topic has attained considerable interest also outside our research community. The aim of this study is to chart the dissemination and diffusion process of h-related literature among communities, disciplines, counties and theory and application. In particular, we would like to answer the question to which extent h-index related research has established as a topic in our field, to which extent application has already passed the borderlines of our field, and is used outside the field of scientometrics and informetrics.
Section snippets
Data retrieval
Distinguishing relevant literature devoted to the h-index, its derivatives and their application, on one hand, from other scientometric and informetric literature and from papers not related to the h-index but using similar terminology or homonyms, on the other hand, proved a multifaceted and time consuming task including much manual work and reading of abstracts and full text of possibly relevant papers. Retrieved literature actually comprises three sets of publications:
The first set of
Methods and results
The objective of this paper is not to develop and to apply any sophisticated diffusion model to our data set. We also resisted the temptation to adopt an existing model from other fields like mathematics, physics or life sciences for an scientometric experiment on the “case” of h-related literature. As mentioned in the introduction section, the aim of this study is to trace the diffusion of h-related literature by scientometric means on the basis of a reliable and representative data source in
Conclusions
Although h-related literature forms a very young research topic in informetrics and scientometrics, it has attracted much interest and provoked extended discussions both within and outside the field. This is reflected by its exceptionally high citation impact which distinctly exceeds that of most other topics in our field. Only network analysis and visualisation techniques exhibit similar success stories. Its simplicity and robustness are certainly responsible for its popularity. However, we
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