In this article, for any group of authors, we define three different h‐indices. First, there is the successive h‐index h2 based on the ranked list of authors and their h‐indices h1 as defined by Schubert (2007). Next, there is the h‐index hP based on the ranked list of authors and their number of publications. Finally, there is the h‐index hC based on the ranked list of authors and their number of citations. We present formulae for these three indices in Lotkaian informetrics from which it also follows that h2 < hp < hc. We give a concrete example of a group of 167 authors on the topic “optical flow estimation.” Besides these three h‐indices, we also calculate the two‐by‐two Spearman rank correlation coefficient and prove that these rankings are significantly related.
Results in the literature concerning the probability that an author publishes r articles in time t are reexamined, and it is found that a negative binomial distribution fits scientific productivity data (by the chi‐squared goodness‐of‐fit test) better than many other distributions such as geometric, logarithmic, zeta, cumulative advantage, etc. It is shown analytically that the negative binomial distribution describes a pattern of scientific productivity under the “success‐breeds‐success” condition in a wide variety of social circumstances.
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