Evolutionary forces in language change
August 02, 2016 ยท Declared Dead ยท ๐ Nature
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Christopher A. Ahern, Mitchell G. Newberry, Robin Clark, Joshua B. Plotkin
arXiv ID
1608.00938
Category
q-bio.PE
Cross-listed
cs.CL
Citations
99
Venue
Nature
Last Checked
1 month ago
Abstract
Languages and genes are both transmitted from generation to generation, with opportunity for differential reproduction and survivorship of forms. Here we apply a rigorous inference framework, drawn from population genetics, to distinguish between two broad mechanisms of language change: drift and selection. Drift is change that results from stochasticity in transmission and it may occur in the absence of any intrinsic difference between linguistic forms; whereas selection is truly an evolutionary force arising from intrinsic differences -- for example, when one form is preferred by members of the population. Using large corpora of parsed texts spanning the 12th century to the 21st century, we analyze three examples of grammatical changes in English: the regularization of past-tense verbs, the rise of the periphrastic `do', and syntactic variation in verbal negation. We show that we can reject stochastic drift in favor of a selective force driving some of these language changes, but not others. The strength of drift depends on a word's frequency, and so drift provides an alternative explanation for why some words are more prone to change than others. Our results suggest an important role for stochasticity in language change, and they provide a null model against which selective theories of language evolution must be compared.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ q-bio.PE
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Simulating COVID-19 in a University Environment
R.I.P.
๐ป
Ghosted
How morphological development can guide evolution
R.I.P.
๐ป
Ghosted
Entropy and Diversity: The Axiomatic Approach
R.I.P.
๐ป
Ghosted
The evolution of conditional moral assessment in indirect reciprocity
R.I.P.
๐ป
Ghosted
Causal Inference in Disease Spread across a Heterogeneous Social System
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted