Using Big Data to Recover Black Women’s Lost History

2019-05-15T00:19:19Z (GMT) by Ruby Mendenhall
Throughout history, Black women’s lived experiences have often been invisible and erased. Therefore, it is important to combat the erasure of Black women and move toward a correction and claiming of their space within the digitized record. This presentation will discuss a study that employs latent dirichlet allocation (LDA) algorithms and comparative text mining to search 800,000 periodicals in JSTOR (Journal Storage) and HathiTrust from 1746 to 2014 to identify the types of conversations that emerge about Black women’s shared experience over time and the resulting knowledge that developed. This presentation will also discuss the potential for seamless creativity and the need to de-mystify advance computing tools across the social sciences and humanities.

ABOUT THE AUTHOR
Ruby Mendenhall is an Associate Professor in Sociology and African American Studies at the University of Illinois, Urbana-Champaign. She is also the Assistant Dean for Diversity and Democratization of Health Innovation at the Carle Illinois College of Medicine. Mendenhall uses mixed methods research to examine how living in racially segregated neighborhoods with high levels of violence affects Black mothers’ mental and physical health. She also studies how racial microaggressions affect students of color health and sense of belonging on predominantly white campuses. She uses advanced computing to recover Black women’s lost history. Her research has appeared in academic journals such as Public Health, Social Forces, Social Science Research, Demography, Housing Policy Debate, The Review of Black Political Economy, The Black Scholar, and Social Service Review.

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CC BY 4.0