An evaluation of author productivity in artificial neural networks research in India during 1991-2014

Kumar, Suresh


The study examines the conformity of Lotka’s law to authorship distribution in the field of Artificial Neural Networks research (ANNs) in India during 1991–2014 using Science Citation Index-Expanded. There were 3411 articles contributed by 5654 unique authors. Lotka’s law was tested using methodology suggested by Pao and compared with maximum likelihood method advocated by Nicholls. The main elements involved in fitting in Lotka’s law were identified. These includes criterion for taking a certain pair of observed data points for calculating Lotka’s gradient, the constant for measurement of single author productivity and assessing goodness-of-fit. The results suggested that author productivity distribution, predicted by the modified Lotka’s Law suggested by Pao, was confirmed to the ANNs discipline in India whereas methodology suggested by Nicholls was not able to explain the author productivity distribution for the same. Evaluation of the prolific authors indicated that most of them are among the top position in their respective institutions. However, they were not listed as first author in their publications supporting that all the authors should be considered while analysing author productivity.


Lotka Law; Bibliometrics; Artificial Neural Networks, India

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