-
Davies, R.: Q-analysis : a methodology for librarianship and information science (1985)
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- Abstract
- Q-analysis is a methodology for investigating a wide range of structural phenomena. Strutures are defined in terms of relations between members of sets and their salient features are revealed using techniques of algebraic topology. However, the basic method can be mastered by non-mathematicians. Q-analysis has been applied to problems as diverse as discovering the rules for the diagnosis of a rare disease and the study of tactics in a football match. Other applications include some of interest to librarians and information scientists. In bibliometrics, Q-analysis has proved capable of emulating techniques such as bibliographic coupling, co-citation analysis and co-word analysis. It has also been used to produce a classification scheme for television programmes based on different principles from most bibliographic classifications. This paper introduces the basic ideas of Q-analysis. Applications relevant to librarianship and information science are reviewed and present limitations of the approach described. New theoretical advances including some in other fields such as planning and design theory and artificial intelligence may lead to a still more powerful method of investigating structure
- Object
- Q-Analysis
-
Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015)
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- Date
- 20. 1.2015 18:30:22
17. 9.2018 18:22:23
-
He, Q.: Knowledge discovery through co-word analysis (1999)
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-
Wu, Q.: ¬The w-index : a measure to assess scientific impact by focusing on widely cited papers (2010)
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- Abstract
- Based on the principles of the h-index, I propose a new measure, the w-index, as a particularly simple and more useful way to assess the substantial impact of a researcher's work, especially regarding excellent papers. The w-index can be defined as follows: If w of a researcher's papers have at least 10w citations each and the other papers have fewer than 10(w+1) citations, that researcher's w-index is w. The results demonstrate that there are noticeable differences between the w-index and the h-index, because the w-index plays close attention to the more widely cited papers. These discrepancies can be measured by comparing the ranks of 20 astrophysicists, a few famous physical scientists, and 16 Price medalists. Furthermore, I put forward the w(q)-index to improve the discriminatory power of the w-index and to rank scientists with the same w. The factor q is the least number of citations a researcher with w needed to reach w+1. In terms of both simplicity and accuracy, the w-index or w(q)-index can be widely used for evaluation of scientists, journals, conferences, scientific topics, research institutions, and so on.
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Ye, F.Y.: ¬A theoretical approach to the unification of informetric models by wave-heat equations (2011)
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- Abstract
- A simple distribution function f(x, t)=p(x+q)**-ße**alpha*t obeys wave and heat equations, that constructs a theoretical approach to the unification of informetric models, with which we can unify all informetric laws. While its space-type distributions deduce naturally Lotka-type laws in size approaches and Zipf-type laws in rank approaches, its time-type distributions introduce the mechanism of Price-type and Brookes-type laws.
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Kretschmer, H.; Kretschmer, T.: Well-ordered collaboration structures of co-author pairs in journals (2006)
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- Abstract
- In single-authored bibliographies only single scientist distribution can be found. But in multi-authored bibliographies single scientists distribution, pairs distribution, triples distribution, etc., can be presented. Whereas regarding Lotka's law single scientists P distribution (both in single-authored and in multi-authored bibliographies) is of interest, in the future pairs P, Q distribution, triples P, Q, R distribution, etc. should be considered Starting with pair distribution, the following question arises in the present paper: Is there also any regularity or well-ordered structure for the distribution of coauthor pairs in journals in analogy to Lotka's law for the distribution of single authors? Usually, in information science "laws " or "regularities " (for example Lotka's law) are mathematical descriptions of observed data inform of functions; however explanations of these phenomena are mostly missing. By contrast, in this paper the derivation of a formula for describing the distribution of the number of co-author pairs will be presented based on wellknown regularities in socio psychology or sociology in conjunction with the Gestalt theory as explanation for well-ordered collaboration structures and production of scientific literature, as well as derivations from Lotka's law. The assumed regularities for the distribution of co-author pairs in journals could be shown in the co-authorship data (1980-1998) of the journals Science, Nature, Proc Nat Acad Sci USA and Phys Rev B Condensed Matter.
-
Sun, Q.; Shaw, D.; Davis, C.H.: ¬A model for estimating the occurence of same-frequency words and the boundary between high- and low-frequency words in texts (1999)
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He, Q.: ¬A study of the strength indexes in co-word analysis (2000)
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-
Zhang, J.; Yu, Q.; Zheng, F.; Long, C.; Lu, Z.; Duan, Z.: Comparing keywords plus of WOS and author keywords : a case study of patient adherence research (2016)
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Yan, E.; Yu, Q.: Using path-based approaches to examine the dynamic structure of discipline-level citation networks (2016)
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Zhou, Q.; Leydesdorff, L.: ¬The normalization of occurrence and co-occurrence matrices in bibliometrics using Cosine similarities and Ochiai coefficients (2016)
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Wang, Q.: ¬A bibliometric model for identifying emerging research topics (2018)
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-
Sarabia, J.M.; Sarabia, M.: Explicit expressions for the Leimkuhler curve in parametric families (2008)
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- Abstract
- In this paper we obtain the Leimkuhler curve in the case of some important statistical distributions proposed in the informetrics and econometrics literature. In this way, we complete the previous work of Burrell [Burrell, Q. L. (2005). Symmetry and other transformation features of Lorenz/Leimkuhler representations of informetric data. Information Processing and Management, 41, 1317-1329], where several open problems were stated. To do this, we use a recent and general definition of the Leimkuhler curve proposed by Sarabia [Sarabia, J. M. (2008a). A general definition of the Leimkuhler curve. Journal of Informetrics, 2, 156-163], and a new representation of the Leimkuhler curve in terms of the first-moment distribution of the population. Specifically, we obtain the Leimkuhler curve of the following distributions: classical and exponentiated Pareto distributions; three-parameter lognormal distribution; generalized gamma distribution, which includes to the exponential and classical gamma distributions among others; generalized beta distribution of the first kind and generalized beta distribution of the second kind, which includes as particular or limiting cases next important families like beta distribution of the second kind, Singh-Maddala, Dagum, Fisk or Lomax distributions. All the obtained Leimkuhler curves can be computed easily.
-
Peng, T.-Q.; Zhu, J.J.H.: Where you publish matters most : a multilevel analysis of factors affecting citations of internet studies (2012)
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-
Naidoo, J.; Huber, J.T.; Cupp, P.; Wu, Q.: Modeling the relationship between an emerging infectious disease epidemic and the body of scientific literature associated with it : the case of HIV/AIDS in the United States (2013)
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-
Ping, Q.; He, J.; Chen, C.: How many ways to use CiteSpace? : a study of user interactive events over 14 months (2017)
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-
Zhang, P.; Wang, OP.; Wu, Q.: How are the best JASIST papers cited? (2018)
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-
Min, C.; Ding, Y.; Li, J.; Bu, Y.; Pei, L.; Sun, J.: Innovation or imitation : the diffusion of citations (2018)
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- Abstract
- Citations in scientific literature are important both for tracking the historical development of scientific ideas and for forecasting research trends. However, the diffusion mechanisms underlying the citation process remain poorly understood, despite the frequent and longstanding use of citation counts for assessment purposes within the scientific community. Here, we extend the study of citation dynamics to a more general diffusion process to understand how citation growth associates with different diffusion patterns. Using a classic diffusion model, we quantify and illustrate specific diffusion mechanisms which have been proven to exert a significant impact on the growth and decay of citation counts. Experiments reveal a positive relation between the "low p and low q" pattern and high scientific impact. A sharp citation peak produced by rapid change of citation counts, however, has a negative effect on future impact. In addition, we have suggested a simple indicator, saturation level, to roughly estimate an individual article's current stage in the life cycle and its potential to attract future attention. The proposed approach can also be extended to higher levels of aggregation (e.g., individual scientists, journals, institutions), providing further insights into the practice of scientific evaluation.
-
Zhang, Q.; Xue, H.; Tang, H.: Knowledge domain and emerging trends in vulnerability assessment in the context of climate change : a bibliometric analysis (1991-2017) (2018)
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He, J.; Ping, Q.; Lou, W.; Chen, C.: PaperPoles : facilitating adaptive visual exploration of scientific publications by citation links (2019)
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