Name-ethnicity classification from open sources

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. Categories and Subject Descriptors I.2.1 [Applications and Expert Systems]: Cartography General Terms Algorithms, Experimentation Keywords ethnicity detection, name classification, news analysis, social science research

• Type: Conference
• Year: 2009
• Where: KDD
• Authors: Anurag Ambekar, Charles B. Ward, Jahangir Mohammed, Steven Skiena, Swapna Male
• Keywords: Accuracy Comparable Accuracy, Classifier Uses, Data Mining, Ethnicity Classifier, KDD 2009