Name-ethnicity classification from open sources

Authors:
Anurag Ambekar;Charles Ward;Jahangir Mohammed;Swapna Male;Steven Skiena
Affiliations:
Stony Brook University, Stony Brook, NY, USA;Stony Brook University, Stony Brook, NY, USA;Stony Brook University, Stony Brook, NY, USA;Stony Brook University, Stony Brook, NY, USA;Stony Brook University, Stony Brook, NY, USA
Venue:
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Year:
2009

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Abstract

The problem of ethnicity identification from names has a variety of important applications, including biomedical research, demographic studies, and marketing. Here we report on the development of an ethnicity classifier where all training data is extracted from public, non-confidential (and hence somewhat unreliable) sources. Our classifier uses hidden Markov models (HMMs) and decision trees to classify names into 13 cultural/ethnic groups with individual group accuracy comparable accuracy to earlier binary (e.g., Spanish/non-Spanish) classifiers. We have applied this classifier to over 20 million names from a large-scale news corpus, identifying interesting temporal and spatial trends on the representation of particular cultural/ethnic groups.