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.
Algorithmic content moderation: Technical and political challenges in the automation of platform governance
2020423 citationsRobert Gorwa, Reuben Binns et al.Big Data & Societyprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Reuben Binns'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 Reuben Binns with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reuben Binns more than expected).
This network shows the impact of papers produced by Reuben Binns. 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 Reuben Binns. The network helps show where Reuben Binns may publish in the future.
Co-authorship network of co-authors of Reuben Binns
This figure shows the co-authorship network connecting the top 25 collaborators of Reuben Binns.
A scholar is included among the top collaborators of Reuben Binns 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 Reuben Binns. Reuben Binns is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Binns, Reuben. (2021). Analogies and Disanalogies Between Machine-Driven and Human-Driven Legal Judgement. 1(1).11 indexed citations
3.
Gorwa, Robert, Reuben Binns, & Christian Katzenbach. (2020). Algorithmic content moderation: Technical and political challenges in the automation of platform governance. Big Data & Society. 7(1). 1245960482–1245960482.423 indexed citations breakdown →
Lindley, Joseph, et al.. (2019). The Little Book of Philosophy for the Internet of Things. Lancaster EPrints (Lancaster University).4 indexed citations
Kleek, Max Van, William Seymour, Michael Veale, Reuben Binns, & Nigel Shadbolt. (2018). The Need for Sensemaking in Networked Privacy and Algorithmic Responsibility. UCL Discovery (University College London).2 indexed citations
10.
Binns, Reuben, Max Van Kleek, Michael Veale, et al.. (2018). 'It's Reducing a Human Being to a Percentage'; Perceptions of Procedural Justice in Algorithmic Decisions. UCL Discovery (University College London).2 indexed citations
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.