Does one novelty lead to another?

Barbar Jazney summarizes interesting work by Tria et al.:

Life would be boring if things were always the same. Tria and colleagues explore whether novelties—discoveries of things new to us—are independent of each other or whether one novelty leads to another. They analyzed selected text, online music, Wikipedia, and a social tagging site and measured how the number of different elements grew with time. Although two of the data sets contained innovations (items new to everyone) and two contained novelties (items new to individual users), they all showed the same kinetics and probability distributions. Modeling analyses suggested that novelties are not independent of each other. As the authors state, each novelty “comes with a cloud of other potentially new ideas that are thematically adjacent to it and hence can be triggered by it.”

Here is the Tria et al. article abstract:

Novelties are a familiar part of daily life. They are also 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 (Heaps' law) and for the probability distribution on the space explored (Zipf's law), as well as signatures of the 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 adjacent possible and its role in biological, cultural, and technological evolution.