Danielle Dean

7 papers and 135 indexed citations i.

About

Danielle Dean is a scholar working on Statistics and Probability, Sociology and Political Science and Artificial Intelligence. According to data from OpenAlex, Danielle Dean has authored 7 papers receiving a total of 135 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Statistics and Probability, 1 paper in Sociology and Political Science and 1 paper in Artificial Intelligence. Recurrent topics in Danielle Dean’s work include Statistical Methods and Bayesian Inference (2 papers), Tendon Structure and Treatment (1 paper) and Social Capital and Networks (1 paper). Danielle Dean is often cited by papers focused on Statistical Methods and Bayesian Inference (2 papers), Tendon Structure and Treatment (1 paper) and Social Capital and Networks (1 paper). Danielle Dean collaborates with scholars based in United States and Italy. Danielle Dean's co-authors include Daniel J. Bauer, David B. Thordarson, Veronica T. Cole, Michael J. Shanahan, Robert A. Zucker, Nisha C. Gottfredson, Wee Hyong Tok, Mathew Salvaris, Mitchell J. Prinstein and Jason D. Boardman and has published in prestigious journals such as Addiction, Psychological Methods and Multivariate Behavioral Research.

In The Last Decade

Co-authorship network of co-authors of Danielle Dean i

Fields of papers citing papers by Danielle Dean

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Danielle Dean. 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 Danielle Dean. The network helps show where Danielle Dean may publish in the future.

Countries citing papers authored by Danielle Dean

Since Specialization
Citations

This map shows the geographic impact of Danielle Dean'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 Danielle Dean with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle Dean more than expected).

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.

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2025