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Evolution of language: An empirical study at eBay Big Data Lab.
David Bodoff1, Ron Bekkerman2, Julie Dai3
1Department of Business Administration, University of Haifa, Haifa, Israel.
Plos One
|December 21, 2017
Summary
Language evolution theory suggests fewer synonyms over time. This study of eBay data shows word usage becoming more precise and similar between buyers and sellers, supporting the theory.
Area of Science:
- Linguistics
- Evolutionary Biology
- Computational Social Science
Background:
- The evolutionary theory of language posits that languages simplify over time, reducing synonymy for objects.
- Empirical validation of language evolution theories often requires large-scale, real-world data.
Purpose of the Study:
- To empirically test predictions of the evolutionary theory of language using large-scale transactional data.
- To investigate changes in word usage and synonymy in a natural language environment.
Main Methods:
- Analysis of word usage in item titles and consumer searches from the eBay Big Data Lab.
- Quantitative assessment of the mapping between objects and words over time.
- Comparison of word usage patterns between vendors and consumers.
Main Results:
- Significant support found for the evolutionary theory of language's predictions.
- The mapping from objects to words became more precise over time for both vendors and consumers.
- Word usage patterns between buyers and sellers demonstrated increasing similarity over time.
Conclusions:
- The study provides large-scale empirical evidence supporting the evolutionary theory of language.
- Language, in this context, shows a trend towards increased specificity and convergence in word use.
- Real-world market data offers a unique lens for studying language evolution.
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