  One new thing often leads to another. Such correlated novelties are a
familiar part of daily life. They are also thought to be fundamental to the
evolution of biological systems, human society, and technology. By opening new
possibilities, one novelty can pave the way for others in a process that
Kauffman has called "expanding the adjacent possible". The dynamics of
correlated novelties, however, have yet to be quantified empirically or modeled
mathematically. Here we propose a simple mathematical model that mimics the
process of exploring a physical, biological or conceptual space that enlarges
whenever a novelty occurs. The model, a generalization of Polya's urn, predicts
statistical laws for the rate at which novelties happen (analogous to Heaps'
law) and for the probability distribution on the space explored (analogous to
Zipf's law), as well as signatures of the hypothesized process by which one
novelty sets the stage for another. We test these predictions on four data sets
of human activity: the edit events of Wikipedia pages, the emergence of tags in
annotation systems, the sequence of words in texts, and listening to new songs
in online music catalogues. By quantifying the dynamics of correlated
novelties, our results provide a starting point for a deeper understanding of
the ever-expanding adjacent possible and its role in biological, linguistic,
cultural, and technological evolution.
