Feminist Data Studies and the emergence of a new Data Feminist knowledge domain

Abstract

Mass participation in social networking sites and online life combined with the development of tracking technology facilitates gathering data on unprecedented scales. The uptake of data collecting during the 2010s coincided with the emergence of data science and data studies, along with critical perspectives such as critical data and critical algorithm studies. This paper explores one such critical perspective. Data Feminism merges the theories of intersectional feminism and critical data studies. Bibliometric text analysis of articles, conference papers, essays, and commentary was conducted in VOSviewer software, which found commonalities between terms within texts. The most prominent terms and keywords in the research area of Data Feminism identified in such a manner informed the close reading that followed. Six clusters of terms were identified, with the two largest clusters formed around the terms “big data” and “artificial intelligence” respectively. We also explored the boundaries, movements and centralities within the six clusters.

'The fall of a dry leaf is a warning to the green ones': Exploring the Twitter ban and the impending dangers of data politics, algorithmic governance, and mass surveillance in Nigeria

“…Algorithms have become an integral part of our daily lives. We are still attempting to understand heir effects on society (Woolley, 2016; Marčetić and Nolin, 2017;van Es, et al, 2021). Algorithms actually have become nearly indispensable in our data-saturated world, from social media feeds and customized search engine recommendations to airport flight schedules, credit checks, financial trading decisions (Gillespie, 2014), traffic control (Wijermars and Makhortykh, 2022), and medical interventions (Masso, et al, 2022).…”