A Novel Method for Analysing Racial Bias: Collection of Person Level References: Appendix: Wikidata

Written by escholar | Published 2024/05/14
Tech Story Tags: natural-language-processing | analysing-racial-bias | time-adjusted-toxicity | semantic-axes | socio-political-changes | google-ngrams-data | sentiment-analysis | bias-in-literature

TLDRIn this study, researchers propose a novel method to analyze representations of African Americans and White Americans in books between 1850 to 2000.via the TL;DR App

This paper is available on arxiv under CC 4.0 license.

Authors:

(1) Muhammed Yusuf Kocyigit, Boston University;

(2) Anietie Andy, University of Pennsylvania;

(3) Derry Wijaya, Boston University.

Table of Links

Appendix: Wikidata

We use the the query in Figure 8 to select the set of individuals that were born in, residents of and citizens of the United States of America. The query takes the ethnic label manually. The ethnic label returns classes that are much more fine-grained then we aim for in this study so we manually create a dictionary to map each sub-group into our main categories presented in Figure 4 as African American, White American and Others. For African American the main rule was that the origin country for the ethnicity would be in the African Continent. We have also classified each European American(for example Italian American, Irish American etc.) ethnicity into White Americans.

Finally we manually label individuals that are are significant figures that don’t contain the ethnicity label in their Wikipedia page. This was more prevalent in White Americans.


Written by escholar | We publish the best academic work (that's too often lost to peer reviews & the TA's desk) to the global tech community
Published by HackerNoon on 2024/05/14