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

Torvik, Vetle I.; Agarwal, Sneha

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https://hdl.handle.net/2142/88927 Copy

Description

Title

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

Author(s)

• Torvik, Vetle I.
• Agarwal, Sneha

Issue Date

2016-03

Keyword(s)

• bibliometrics
• ethnicity classification
• machine learning

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

Type of Resource

text

Language

en

Permalink

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

Sponsor(s)/Grant Number(s)

• NIH P01AG039347
• NSF 1348742

Owning Collections