Munich Personal RePEc Archive

Behavior Mining in h-index Ranking Game

Tagiew, Rustam and Ignatov, Dmitry I. (2017): Behavior Mining in h-index Ranking Game. Published in: CEUR Workshop Proceeding , Vol. 1968, No. Experimental Economics and Machine Learning (28 October 2017): pp. 52-61.

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Abstract

Academic rewards and honors are proven to correlate with h-index, although it was not the decision criterion for them till recent years. Once h-index becomes the rule-setting scientometric ranking measure in the zero-sum game for academic positions and research resources as suggested by its advocates, the rational behavior of competing academics is expected to converge towards its game-theoretic solution. This paper derives the game-theoretic solution, its evidence in scientometric data and discusses its consequences on the development of science. DBLP database of 07/2017 was used for mining. Additionally, the openly available scientometric datasets are introduced as a good alternative to commercial datasets of comparable size for public research in behavioral sciences.

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