Mike Dowman

817 total citations · 1 hit paper
16 papers, 451 citations indexed

About

Mike Dowman is a scholar working on Experimental and Cognitive Psychology, Artificial Intelligence and Cultural Studies. According to data from OpenAlex, Mike Dowman has authored 16 papers receiving a total of 451 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Experimental and Cognitive Psychology, 4 papers in Artificial Intelligence and 3 papers in Cultural Studies. Recurrent topics in Mike Dowman's work include Categorization, perception, and language (9 papers), Multisensory perception and integration (6 papers) and Language and cultural evolution (3 papers). Mike Dowman is often cited by papers focused on Categorization, perception, and language (9 papers), Multisensory perception and integration (6 papers) and Language and cultural evolution (3 papers). Mike Dowman collaborates with scholars based in United States, Japan and Australia. Mike Dowman's co-authors include Thomas L. Griffiths, Simon Kirby, Jing Xu, Borislav Popov, Valentin Tablan, Hamish Cunningham, Virginia Savova, Konrad P. Körding, Matthew Purver and Joshua B. Tenenbaum and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Proceedings of the Royal Society B Biological Sciences and Cognitive Science.

In The Last Decade

Mike Dowman

14 papers receiving 418 citations

Hit Papers

Innateness and culture in the evolution of language 2007 2026 2013 2019 2007 50 100 150 200

Peers

Mike Dowman
Jinyun Ke United States
Steven Moran Switzerland
Andreea S. Calude New Zealand
Joe Jackson United States
Lyle Jenkins Austria
Haim Dubossarsky United Kingdom
Mike Dowman
Citations per year, relative to Mike Dowman Mike Dowman (= 1×) peers Christian Bentz

Countries citing papers authored by Mike Dowman

Since Specialization
Citations

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

Fields of papers citing papers by Mike Dowman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mike Dowman

This figure shows the co-authorship network connecting the top 25 collaborators of Mike Dowman. A scholar is included among the top collaborators of Mike Dowman 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 Mike Dowman. Mike Dowman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Xu, Jing, Mike Dowman, & Thomas L. Griffiths. (2013). Cultural transmission results in convergence towards colour term universals. Proceedings of the Royal Society B Biological Sciences. 280(1758). 20123073–20123073. 42 indexed citations
2.
Xu, Jing, Thomas L. Griffiths, & Mike Dowman. (2010). Replicating Color Term Universals through Human Iterated Learning. eScholarship (California Digital Library). 32(32). 5 indexed citations
3.
Dowman, Mike. (2008). The Nature of Words in Human Protolanguages: It's Not a Holophrastic-Atomic Meanings Dichotomy. Artificial Life. 14(4). 445–465. 5 indexed citations
4.
Dowman, Mike, Jing Xu, & Thomas L. Griffiths. (2008). A HUMAN MODEL OF COLOR TERM EVOLUTION. The Evolution of Language. 421–422. 2 indexed citations
6.
Dowman, Mike. (2007). Explaining Color Term Typology With an Evolutionary Model. Cognitive Science. 31(1). 99–132. 32 indexed citations
7.
Kirby, Simon, Mike Dowman, & Thomas L. Griffiths. (2007). Innateness and culture in the evolution of language. Proceedings of the National Academy of Sciences. 104(12). 5241–5245. 249 indexed citations breakdown →
8.
Dowman, Mike. (2007). Explaining Color Term Typology With an Evolutionary Model. Cognitive Science. 30(1). 99–132. 4 indexed citations
9.
Dowman, Mike, Simon Kirby, & Thomas L. Griffiths. (2006). INNATENESS AND CULTURE IN THE EVOLUTION OF LANGUAGE. The Evolution of Language. 83–90. 22 indexed citations
10.
Dowman, Mike. (2006). A Bayesian Approach To Colour Term Semantics.
11.
Dowman, Mike, Valentin Tablan, Hamish Cunningham, & Borislav Popov. (2005). Web-assisted annotation, semantic indexing and search of television and radio news. 225–225. 47 indexed citations
12.
Dowman, Mike. (2005). Investigating the Effect of Random Noise on the Evolution of Colour Terms. 1. 581–587. 1 indexed citations
13.
Dowman, Mike, Valentin Tablan, Hamish Cunningham, & Borislav Popov. (2005). Content Augmentation for Mixed-Mode News Broadcasts. 3 indexed citations
14.
Dowman, Mike. (2004). Colour Terms, Syntax and Bayes Modelling Acquisition and Evolution. The Sydney eScholarship Repository (The University of Sydney). 1 indexed citations
15.
Dowman, Mike. (2003). Explaining Color Term Typology as the Product of Cultural Evolution using a Bayesian Multi-agent Model. eScholarship (California Digital Library). 25(25). 2 indexed citations
16.
Dowman, Mike. (2000). Addressing the Learnability of Verb Subcategorization with Bayesian Inference. eScholarship (California Digital Library). 22(22). 21 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.

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