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Social media enhances languages differentiation: a mathematical description
Ignacio Vidal-Franco1, Jacobo Guiu-Souto1,2, Alberto P Muñuzuri1
1Group of NonLinear Physics, Universidade Santiago de Compostela, 15706 Santiago de Compostela, Spain.
High social network connectivity can surprisingly lead to language differentiation, not homogenization. This study models competing language evolution, revealing how network structure impacts linguistic diversity.
Area of Science:
- Sociolinguistics
- Computational Linguistics
- Mathematical Modeling
Background:
- The world has over 6000 languages in a highly connected environment.
- Understanding language evolution and competition is crucial.
Purpose of the Study:
- To analyze the effect of speaker connectivity on the evolution of competing languages.
- To investigate the role of social networks in language dynamics.
Main Methods:
- Developed a mathematical model for two competing languages.
- Simulated language competition under varying connectivity levels.
Main Results:
- High connectivity did not lead to homogenization as expected.
- Specific parameters with high connectivity promoted language differentiation.
- Social network structure significantly influences linguistic diversity.
Conclusions:
- Connectivity's impact on language competition is complex and parameter-dependent.
- High connectivity can foster linguistic diversity under certain conditions.
- Mathematical models are valuable for understanding sociolinguistic phenomena.
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