EARLY DETECTION OF FACTORS, INCLUDING PANDEMICS AND DISASTERS, LEADING TO LANGUAGE ENDANGERMENT:  THINKING STATISTICALLY

Deepak Sharma

doi:10.51611/iars.irj.v11i1.2021.153

Authors

Deepak Sharma Institute of Innovation, Technology and Management, New Delhi, India

DOI:

https://doi.org/10.51611/iars.irj.v11i1.2021.153

Keywords:

Computational Intelligence, Language Endangerment, Computing, Testing

Abstract

The target of this research work is to use a statistical technique on different languages to identify significant factors of endangered languages with similar characteristics to build a model for language endangerment. Factor analysis is used to identify factors. The factors are used to construct a model with and without interaction terms. First three variables (i.e. speakers, longitude and latitude) are analyzed to identify two factors and then these three variables and three interaction terms are used to construct the model. Different variables were identified and a model with and without interaction terms is built using the identified factors. The result shows that the model has significant predictive power. The predictors were retrieved from the dataset. The outcome encourages future studies towards defining techniques of language endangerment prediction for analyzing factors of language endangerment.

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