Rethnicity: Predicting Ethnicity from Names
This provides a tool for researchers and practitioners in social sciences or data analysis to infer ethnicity from names, but it is incremental as it builds on existing methods and datasets.
The authors tackled the problem of predicting ethnicity from names by developing an R package that uses a Bidirectional LSTM model trained on Florida Voter Registration data, with adjustments for minority group accuracy, and achieved competitive performance compared to other solutions.
In this study, a new R package, \texttt{rethnicity} is provided for predicting ethnicity based on names. The Bidirectional LSTM and Florida Voter Registration were used as the model and training data, respectively. Special care was given for the accuracy of minority groups, by adjusting the imbalance in the dataset. The models were trained and exported to C++ and then integrated with R using Rcpp. Additionally, the availability, accuracy, and performance of the package were compared with other solutions.