A class of urn-based models accounts for stochastic regularities observed in systems that exhibit innovation in diverse forms and temporal scales, from the appearance of new organisms to the evolution of language to daily new experiences. The authors investigate the predictive power of those models in inference problems, addressing the authorship attribution task as a case study.
- Giulio Tani Raffaelli
- Margherita Lalli
- Francesca Tria
