
arXiv: 1711.06899
We explore how ideas from infectious disease and genetics can be used to uncover patterns of cultural inheritance and innovation in a corpus of 591 national constitutions spanning 1789–2008. Legal “ideas” are encoded as “topics”—words statistically linked in documents—derived from topic modeling the corpus of constitutions. Using these topics we derive a diffusion network for borrowing from ancestral constitutions back to the US Constitution of 1789 and reveal that constitutions are complex cultural recombinants. We find systematic variation in patterns of borrowing from ancestral texts and “biological”‐like behavior in patterns of inheritance, with the distribution of “offspring” arising through a bounded preferential‐attachment process. This process leads to a small number of highly innovative (influential) constitutions some of which have yet to have been identified as so in the current literature. Our findings thus shed new light on the critical nodes of the constitution‐making network. The constitutional network structure reflects periods of intense constitution creation, and systematic patterns of variation in constitutional lifespan and temporal influence.
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Computer Science - Computation and Language, J.4, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), 68.U99, Computation and Language (cs.CL)
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Computer Science - Computation and Language, J.4, FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), 68.U99, Computation and Language (cs.CL)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 29 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
