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  • × author_ss:"Burrell, Q.L."
  • × theme_ss:"Informetrie"
  1. Burrell, Q.L.: Measuring similarity of concentration between different informetric distributions : two new approaches (2005) 0.01 
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    Abstract
    From its earliest days, much investigative work in informetrics has been concerned with inequality aspects. Beginning with the weIl-known Gin! coefficient as a measure of the concentration/inequality of productivity within a single data set, in this study we look at the problem of measuring relative inequallty of productivity between two data sets. A measure originally proposed by Dagum (1987), analogous to the Gin! coefficient, is discussed and developed with both theoretical and empir!cal illustrations. From this we derive a standardized measure-the relative concentration coefficient-based an the notion of "relative economic affluence" also introduced by Dagum (1987). Finally, a new standardized measure-the co-concentration coefficient, in some ways analogous to the correlation coefficient-is defined. The merits and drawbacks of these two measures are discussed and illustrated. Their value will be most readily appreclated in comparative empirical studies.
  2. Burrell, Q.L.: Extending Lotkaian informetrics (2008) 0.01 
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    Abstract
    The continuous version of the Lotka distribution, more generally referred to outside of informetrics as the Pareto distribution, has long enjoyed a central position in the theoretical development of informetrics despite several reported drawbacks in modelling empirical data distributions, most particularly that the inverse power form seems mainly to be evident only in the upper tails. We give a number of published examples graphically illustrating this shortcoming. In seeking to overcome this, we here draw attention to an intuitively reasonable generalization of the Pareto distribution, namely the Pareto type II distribution, of which we consider two versions. We describe its basic properties and some statistical features together with concentration aspects and argue that, at least in qualitative terms, it is better able to describe many observed informetric phenomena over the full range of the distribution. Suggestions for further investigations, including truncated and time-dependent versions, are also given.
  3. Burrell, Q.L.: Predicting future citation behavior (2003) 0.01 
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    Date
    29. 3.2003 19:22:48
  4. Mingers, J.; Burrell, Q.L.: Modeling citation behavior in Management Science journals (2006) 0.00 
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    Date
    26.12.2007 19:22:05