Rethnicity: Predicting Ethnicity from Names
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Abstract (arXiv)
In this study, a new R package, textttrethnicity 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.
Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 5 of its 28 references that are in the map. First posted on arXiv 19 Sep 2021.
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5 of 28 references.
References · 5
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,304
- 2015Distilling the Knowledge in a Neural Networkcited by 10,180
- 2015Character-level Convolutional Networks for Text Classificationcited by 2,319
- 2021ByT5: Towards a token-free future with pre-trained byte-to-byte modelscited by 507
- 2018Predicting Race and Ethnicity From the Sequence of Characters in a Namecited by 25
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