Name-ethnicity classification from open sources

Anurag Ambekar; Charles Ward; Jahangir Mohammed; Swapna Male; Steven Skiena

doi:10.1145/1557019.1557032

Name-ethnicity classification from open sources

Anurag Ambekar
, Charles Ward
, Jahangir Mohammed
, Swapna Male
, Steven Skiena

Computer Science

Stony Brook University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

166 Scopus citations

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.

Original language	English
Title of host publication	KDD '09
Subtitle of host publication	Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Pages	49-57
Number of pages	9
DOIs	https://doi.org/10.1145/1557019.1557032
State	Published - 2009
Event	15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '09 - Paris, France Duration: Jun 28 2009 → Jul 1 2009

Publication series

Name	Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Conference

Conference	15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '09
Country/Territory	France
City	Paris
Period	06/28/09 → 07/1/09

Keywords

Ethnicity detection
Name classification
News analysis
Social science research

Access to Document

10.1145/1557019.1557032

Cite this

Ambekar, A., Ward, C., Mohammed, J., Male, S., & Skiena, S. (2009). Name-ethnicity classification from open sources. In KDD '09: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 49-57). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). https://doi.org/10.1145/1557019.1557032

@inproceedings{fc913b47fff7407da2f22cba48b489c0,

title = "Name-ethnicity classification from open sources",

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.",

keywords = "Ethnicity detection, Name classification, News analysis, Social science research",

author = "Anurag Ambekar and Charles Ward and Jahangir Mohammed and Swapna Male and Steven Skiena",

year = "2009",

doi = "10.1145/1557019.1557032",

language = "English",

isbn = "9781605584959",

series = "Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",

pages = "49--57",

booktitle = "KDD '09",

note = "15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '09 ; Conference date: 28-06-2009 Through 01-07-2009",

}

Ambekar, A, Ward, C, Mohammed, J, Male, S & Skiena, S 2009, Name-ethnicity classification from open sources. in KDD '09: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 49-57, 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '09, Paris, France, 06/28/09. https://doi.org/10.1145/1557019.1557032

Name-ethnicity classification from open sources. / Ambekar, Anurag; Ward, Charles; Mohammed, Jahangir et al.
KDD '09: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2009. p. 49-57 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Name-ethnicity classification from open sources

AU - Ambekar, Anurag

AU - Ward, Charles

AU - Mohammed, Jahangir

AU - Male, Swapna

AU - Skiena, Steven

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

KW - Ethnicity detection

KW - Name classification

KW - News analysis

KW - Social science research

UR - https://www.scopus.com/pages/publications/70350694226

U2 - 10.1145/1557019.1557032

DO - 10.1145/1557019.1557032

M3 - Conference contribution

AN - SCOPUS:70350694226

SN - 9781605584959

T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

SP - 49

EP - 57

BT - KDD '09

T2 - 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '09

Y2 - 28 June 2009 through 1 July 2009

ER -

Name-ethnicity classification from open sources

Abstract

Publication series

Conference

Keywords

Access to Document

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