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Subdiffusive semantic evolution in Indo-European languages

arXiv 2209.04701 ↗First posted 10 Sep 2022physics.soc-ph cs.CLcited by 0

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Abstract (arXiv)

How do words change their meaning? Although semantic evolution is driven by a variety of distinct factors, including linguistic, societal, and technological ones, we find that there is one law that holds universally across five major Indo-European languages: that semantic evolution is strongly subdiffusive. Using an automated pipeline of diachronic distributional semantic embedding that controls for underlying symmetries, we show that words follow stochastic trajectories in meaning space with an anomalous diffusion exponent α= 0.45± 0.05 across languages, in contrast with diffusing particles that follow α=1. Randomization methods indicate that preserving temporal correlations in semantic change directions is necessary to recover strongly subdiffusive behavior; however, correlations in change sizes play an important role too. We furthermore show that strong subdiffusion is a robust phenomenon under a wide variety of choices in data analysis and interpretation, such as the choice of fitting an ensemble average of displacements or averaging best-fit exponents of individual word trajectories.

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References · 9

  1. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  2. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,474
  3. 2016Diachronic Word Embeddings Reveal Statistical Laws of Semantic Changecited by 221
  4. 2014word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding methodcited by 112
  5. 2017Dynamic Word Embeddingscited by 51
  6. 2017Dynamic Word Embeddings for Evolving Semantic Discoverycited by 38
  7. 2021A comparative evaluation and analysis of three generations of Distributional Semantic Modelscited by 19
  8. 2015Characterizing the Google Books corpus: Strong limits to inferences of socio-cultural and linguistic evolutioncited by 15
  9. 2014Zipf's law holds for phrases, not wordscited by 12

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