  Our quantitative understanding of how scientists choose and shift their
research focus over time is highly consequential, because it affects the ways
in which scientists are trained, science is funded, knowledge is organized and
discovered, and excellence is recognized and rewarded. Despite extensive
investigations of various factors that influence a scientist's choice of
research topics, quantitative assessments of mechanisms that give rise to
macroscopic patterns characterizing research interest evolution of individual
scientists remain limited. Here we perform a large-scale analysis of
publication records, finding that research interest change follows a
reproducible pattern characterized by an exponential distribution. We identify
three fundamental features responsible for the observed exponential
distribution, which arise from a subtle interplay between exploitation and
exploration in research interest evolution. We develop a random walk based
model, allowing us to accurately reproduce the empirical observations. This
work presents a quantitative analysis of macroscopic patterns governing
research interest change, discovering a high degree of regularity underlying
scientific research and individual careers.
