  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.
