A Markov-switching approach to the study of citations in academic journals

FERNANDO ANDRÉS DELBIANCO; ANDRÉS FIORITI; HERNANDEZ-CHANTO, ALLAN; FERNANDO ABEL TOHMÉ

Journal of Informetrics

Elsevier B.V.

Año: 2020 vol. 14

1751-1577

In this paper, we introduce a Markovian approach to study the stability and growth of citations in academic journals by featuring a regime-switching analysis. We characterize the regime structure exhibited by the series of citations available in the Web of Science database and determine the series? transition probabilities across regimes. Our main result shows that for most of the journals studied, the series of citations exhibit a stable growth, remaining majorly in a dominant regime identified as one of low or high number of citations.