Testing Lotka's Law and Pattern of Author Productivity in the Scholarly\n Publications of Artificial Intelligence

Abstract

Artificial intelligence has changed our day to day life in multitude ways. AI\ntechnology is rearing itself as a driving force to be reckoned with in the\nlargest industries in the world. AI has already engulfed our educational\nsystem, our businesses and our financial establishments. The future is definite\nthat machines with artificial intelligence will soon be captivating over\ntrained manual work that now is mostly cared by humans. Machines can carry out\nhuman-like tasks by new inputs as artificial intelligence makes it possible for\nmachines to learn from experience. AI data from web of science database from\n2008 to 2017 have been mapped to depict the average growth rate, relative\ngrowth rate, contribution made by authors in the view of research productivity,\nauthorship pattern and collaboration of AI literature. The Lotka's law on\nauthorship productivity of AI literature has been tested to confirm the\napplicability of the law to the present data set. A K-S test was applied to\nmeasure the degree of agreement between the distribution of the observed set of\ndata against the inverse general power relationship and the theoretical value\nof {\\alpha} =2. It is found that the inverse square law of Lotka follow as\nsuch.\n

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