Ethnea -- an instance-based ethnicity classifier based on geo-coded author names in a large-scale bibliographic database

Vetle Ingvald Torvik; Sneha Agarwal

Ethnea -- an instance-based ethnicity classifier based on geo-coded author names in a large-scale bibliographic database

School of Information Sciences

Research output: Contribution to conference › Paper › peer-review

Abstract

We present a nearest neighbor approach to ethnicity classification. Given an author name, all of its instances (or the most similar ones) in PubMed are identified and coupled with their respective country of affiliation, and then probabilistically mapped to a set of 26 predefined ethnicities. The dominant ethnicity (or pair of ethnicities) is assigned as the class. The predictions are also used to upgrade Genni (Smith, Singh, and Torvik, 2013) to provide ethnicity-specific gender predictions for cases like Italian vs. English Andrea, Turkish vs. Korean Bora, Israeli vs. Nordic Eli, and Slavic vs. Japanese Renko. Ethnea and Genni 2.0 are available at http://abel.lis.illinois.edu

Original language	English (US)
Number of pages	1
State	Published - Mar 2016
Event	International Symposium on Science of Science - Library of Congress, Washington DC, United States Duration: Mar 22 2016 → Mar 23 2016

Conference

Conference	International Symposium on Science of Science
Country/Territory	United States
City	Washington DC
Period	3/22/16 → 3/23/16

Keywords

bibliometrics
ethnicity classification
machine learning

Library availability

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title = "Ethnea -- an instance-based ethnicity classifier based on geo-coded author names in a large-scale bibliographic database",

abstract = "We present a nearest neighbor approach to ethnicity classification. Given an author name, all of its instances (or the most similar ones) in PubMed are identified and coupled with their respective country of affiliation, and then probabilistically mapped to a set of 26 predefined ethnicities. The dominant ethnicity (or pair of ethnicities) is assigned as the class. The predictions are also used to upgrade Genni (Smith, Singh, and Torvik, 2013) to provide ethnicity-specific gender predictions for cases like Italian vs. English Andrea, Turkish vs. Korean Bora, Israeli vs. Nordic Eli, and Slavic vs. Japanese Renko. Ethnea and Genni 2.0 are available at http://abel.lis.illinois.edu",

keywords = "bibliometrics, ethnicity classification, machine learning",

author = "Torvik, {Vetle Ingvald} and Sneha Agarwal",

year = "2016",

month = mar,

language = "English (US)",

note = "International Symposium on Science of Science ; Conference date: 22-03-2016 Through 23-03-2016",

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TY - CONF

T1 - Ethnea -- an instance-based ethnicity classifier based on geo-coded author names in a large-scale bibliographic database

AU - Torvik, Vetle Ingvald

AU - Agarwal, Sneha

PY - 2016/3

Y1 - 2016/3

N2 - We present a nearest neighbor approach to ethnicity classification. Given an author name, all of its instances (or the most similar ones) in PubMed are identified and coupled with their respective country of affiliation, and then probabilistically mapped to a set of 26 predefined ethnicities. The dominant ethnicity (or pair of ethnicities) is assigned as the class. The predictions are also used to upgrade Genni (Smith, Singh, and Torvik, 2013) to provide ethnicity-specific gender predictions for cases like Italian vs. English Andrea, Turkish vs. Korean Bora, Israeli vs. Nordic Eli, and Slavic vs. Japanese Renko. Ethnea and Genni 2.0 are available at http://abel.lis.illinois.edu

AB - We present a nearest neighbor approach to ethnicity classification. Given an author name, all of its instances (or the most similar ones) in PubMed are identified and coupled with their respective country of affiliation, and then probabilistically mapped to a set of 26 predefined ethnicities. The dominant ethnicity (or pair of ethnicities) is assigned as the class. The predictions are also used to upgrade Genni (Smith, Singh, and Torvik, 2013) to provide ethnicity-specific gender predictions for cases like Italian vs. English Andrea, Turkish vs. Korean Bora, Israeli vs. Nordic Eli, and Slavic vs. Japanese Renko. Ethnea and Genni 2.0 are available at http://abel.lis.illinois.edu

KW - bibliometrics

KW - ethnicity classification

KW - machine learning

UR - http://hdl.handle.net/2142/88927

M3 - Paper

T2 - International Symposium on Science of Science

Y2 - 22 March 2016 through 23 March 2016

ER -

Ethnea -- an instance-based ethnicity classifier based on geo-coded author names in a large-scale bibliographic database

Abstract

Conference

Keywords

Library availability

Related links

Fingerprint

Genni + Ethnea for the Author-ity 2009 dataset

Cite this

Ethnea -- an instance-based ethnicity classifier based on geo-coded author names in a large-scale bibliographic database

Abstract

Conference

Keywords

Library availability

Related links

Fingerprint

Datasets

Genni + Ethnea for the Author-ity 2009 dataset

Cite this