Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Big Data's Disparate Impact
20161.1k citationsSolon Barocas, Andrew D. SelbstSSRN Electronic Journalprofile →
Fairness and Abstraction in Sociotechnical Systems
2019589 citationsAndrew D. Selbst, danah boyd et al.profile →
Citations per year, relative to Andrew D. Selbst Andrew D. Selbst (= 1×)
peers
Solon Barocas
Countries citing papers authored by Andrew D. Selbst
Since
Specialization
Citations
This map shows the geographic impact of Andrew D. Selbst's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andrew D. Selbst with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew D. Selbst more than expected).
Fields of papers citing papers by Andrew D. Selbst
This network shows the impact of papers produced by Andrew D. Selbst. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andrew D. Selbst. The network helps show where Andrew D. Selbst may publish in the future.
Co-authorship network of co-authors of Andrew D. Selbst
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew D. Selbst.
A scholar is included among the top collaborators of Andrew D. Selbst based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Andrew D. Selbst. Andrew D. Selbst is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
14 of 14 papers shown
1.
Raji, Inioluwa Deborah, et al.. (2022). The Fallacy of AI Functionality. arXiv (Cornell University). 959–972.104 indexed citations
2.
Selbst, Andrew D.. (2021). An Institutional View Of Algorithmic Impact Assessments. SSRN Electronic Journal.38 indexed citations
3.
Selbst, Andrew D.. (2019). Negligence and AI's Human Users. SSRN Electronic Journal.17 indexed citations
4.
Selbst, Andrew D., danah boyd, Sorelle A. Friedler, Suresh Venkatasubramanian, & Janet Vertesi. (2019). Fairness and Abstraction in Sociotechnical Systems. 59–68.589 indexed citations breakdown →
5.
Selbst, Andrew D.. (2018). Disparate Impact in Big Data Policing. eYLS (Yale Law School). 52(1). 3373.27 indexed citations
6.
Selbst, Andrew D. & Solon Barocas. (2018). The Intuitive Appeal of Explainable Machines. Fordham law review. 87(3). 1085.49 indexed citations
7.
Selbst, Andrew D., danah boyd, Sorelle A. Friedler, Suresh Venkatasubramanian, & Janet Vertesi. (2018). Fairness and Abstraction in Sociotechnical Systems. SSRN Electronic Journal.2 indexed citations
Selbst, Andrew D.. (2011). The Journalism Ratings Board: An Incentive-Based Approach to Cable News Accountability. University of Michigan Journal of Law Reform. 44(2). 467–509.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.