The association between topic growth and citation impact of research publications

Citations are used for research evaluation, and it is therefore important to know which factors influence or associate with citation impact of articles. Several citation factors have been studied in the literature. In this study we propose a new factor, topic growth, that no previous study has studied empirically. The growth rate of topics may influence future citation counts because a high growth in a topic means there are more publications citing previous publications in that topic. We construct topics using community detection in a citation network and use a two-part regression model to study the association between topic growth and citation counts in eight broad disciplines. The first part of the model uses quantile regression to estimate the effect of growth ratio on citation counts for publications with more than three citations. The second part of the model uses logistic regression to model the influence of the explanatory variables on the probability of being lowly cited versus being modestly or highly cited. Both models control for three variables that may distort the association between the topic growth and citations: journal impact, number of references, and number of authors. The regression model clearly shows that publications in fast-growing topics have a citation advantage compared to publications in slow-growing or declining topics in all of the eight disciplines. Using citation indicators for research evaluation may give incentives for researchers to publish in fast-growing topics, but they may cause research to be less diversified. The results have also some implications for citation normalization.