5 citations · 5 across the 3 of their papers we have counts for
5 papers
Lotka's Inverse Square Law of Scientific Productivity: Its Methods and Statistics
Stephen J. Bensman, Lawrence J. Smolinsky
This brief communication analyzes the statistics and methods Lotka used to derive his inverse square law of scientific productivity from the standpoint of modern theory. It finds t…
Power-law distributions, the h-index, and Google Scholar (GS) citations: a test of their relationship with economics Nobelists
Stephen J. Bensman, Alice Daugherty, Lawrence J. Smolinsky +2
This paper presents proof that Google Scholar (GS) can construct documentary sets relevant for evaluating researchers' works. Nobelists in economics were the researchers under anal…
Comparison of the Research Effectiveness of Chemistry Nobelists and Fields Medalist Mathematicians with Google Scholar: the Yule-Simon Model
Stephen J. Bensman, Lawrence J. Smolinsky, Daniel S. Sage
This paper uses the Yule-Simon model to estimate to what extent the work of chemistry Nobelists and Fields medalist mathematicians is incorporated into the knowledge corpus of thei…
Eugene Garfield, Francis Narin, and PageRank: The Theoretical Bases of the Google Search Engine
Stephen J. Bensman
This paper presents a test of the validity of using Google Scholar to evaluate the publications of researchers by comparing the premises on which its search engine, PageRank, is ba…
Classification and Powerlaws: The Logarithmic Transformation
Loet Leydesdorff, Stephen Bensman
Logarithmic transformation of the data has been recommended by the literature in the case of highly skewed distributions such as those commonly found in information science. The pu…