Simon De Deyne

3.7k total citations
69 papers, 2.2k citations indexed

About

Simon De Deyne is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Developmental and Educational Psychology. According to data from OpenAlex, Simon De Deyne has authored 69 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Cognitive Neuroscience, 29 papers in Artificial Intelligence and 20 papers in Developmental and Educational Psychology. Recurrent topics in Simon De Deyne's work include Neurobiology of Language and Bilingualism (26 papers), Topic Modeling (19 papers) and Advanced Text Analysis Techniques (12 papers). Simon De Deyne is often cited by papers focused on Neurobiology of Language and Bilingualism (26 papers), Topic Modeling (19 papers) and Advanced Text Analysis Techniques (12 papers). Simon De Deyne collaborates with scholars based in Belgium, Australia and United States. Simon De Deyne's co-authors include Gert Storms, Marc Brysbaert, Danielle Navarro, Ilse Van Wijnendaele, Amy Perfors, Wouter Voorspoels, Steven Verheyen, Rik Vandenberghe, Rose Bruffaerts and Patrick Dupont and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and NeuroImage.

In The Last Decade

Simon De Deyne

66 papers receiving 2.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Simon De Deyne Belgium 25 1.2k 741 717 580 358 69 2.2k
Gert Storms Belgium 30 1.4k 1.2× 1.3k 1.7× 995 1.4× 1.1k 1.9× 541 1.5× 174 3.7k
Amy Perfors Australia 21 699 0.6× 992 1.3× 755 1.1× 356 0.6× 182 0.5× 71 2.1k
Thomas A. Schreiber United States 13 1.4k 1.2× 706 1.0× 598 0.8× 506 0.9× 393 1.1× 21 2.1k
Moreno I. Coco United Kingdom 17 873 0.7× 752 1.0× 409 0.6× 569 1.0× 354 1.0× 52 2.0k
Amy Beth Warriner Canada 8 1.1k 0.9× 714 1.0× 850 1.2× 1.1k 1.8× 702 2.0× 8 2.8k
Curt Burgess United States 19 1.8k 1.5× 1.2k 1.7× 1.1k 1.6× 821 1.4× 331 0.9× 37 3.2k
Simon Dennis Australia 26 1.4k 1.2× 473 0.6× 702 1.0× 282 0.5× 348 1.0× 107 2.4k
Chris Westbury Canada 26 2.2k 1.8× 1.2k 1.6× 499 0.7× 1.1k 1.9× 556 1.6× 70 3.4k
George S. Cree Canada 11 1.2k 1.0× 813 1.1× 435 0.6× 605 1.0× 575 1.6× 16 1.9k
Hannah Rohde United Kingdom 23 1.3k 1.1× 1.2k 1.7× 1.1k 1.6× 1.0k 1.7× 255 0.7× 89 3.3k

Countries citing papers authored by Simon De Deyne

Since Specialization
Citations

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

Fields of papers citing papers by Simon De Deyne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Simon De Deyne. 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 Simon De Deyne. The network helps show where Simon De Deyne may publish in the future.

Co-authorship network of co-authors of Simon De Deyne

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

All Works

20 of 20 papers shown
1.
Deyne, Simon De, et al.. (2024). A Computational Approach to Identifying Cultural Keywords Across Languages. Cognitive Science. 48(1). e13402–e13402. 1 indexed citations
2.
Deyne, Simon De, et al.. (2023). Towards hypergraph cognitive networks as feature-rich models of knowledge. EPJ Data Science. 12(1). 2 indexed citations
3.
Deyne, Simon De, et al.. (2023). The "Small World of Words" free association norms for Rioplatense Spanish. Behavior Research Methods. 56(2). 968–985. 6 indexed citations
4.
Deyne, Simon De, et al.. (2023). Unraveling lexical semantics in the brain: Comparing internal, external, and hybrid language models. Human Brain Mapping. 45(1). e26546–e26546. 5 indexed citations
5.
Deyne, Simon De, et al.. (2023). The Pandemic in Words: Tracking Fast Semantic Changes via a Large-Scale Word Association Task. Open Mind. 7. 221–239. 3 indexed citations
6.
Cohn, Trevor, et al.. (2022). WAX: A New Dataset for Word Association eXplanations. 106–120. 1 indexed citations
7.
Wong, Ting Yat, Charlton Cheung, Christy Lai Ming Hui, et al.. (2022). Discovering the structure and organization of a free Cantonese emotion-label word association graph to understand mental lexicons of emotions. Scientific Reports. 12(1). 19581–19581. 4 indexed citations
8.
Wulff, Dirk U., Simon De Deyne, Michael N. Jones, & Rui Mata. (2019). New Perspectives on the Aging Lexicon. Trends in Cognitive Sciences. 23(8). 686–698. 97 indexed citations
9.
Dupont, Patrick, Ronald Peeters, Rose Bruffaerts, et al.. (2019). Left perirhinal cortex codes for semantic similarity between written words defined from cued word association. NeuroImage. 191. 127–139. 18 indexed citations
10.
Bruffaerts, Rose, et al.. (2019). Redefining the resolution of semantic knowledge in the brain: Advances made by the introduction of models of semantics in neuroimaging. Neuroscience & Biobehavioral Reviews. 103. 3–13. 29 indexed citations
11.
Deyne, Simon De, Amy Perfors, & Danielle Navarro. (2018). Learning word meaning with little means: An investigation into the inferential capacity of paradigmatic information.. Cognitive Science. 2 indexed citations
12.
Bruffaerts, Rose, Ronald Peeters, Katarzyna Adamczuk, et al.. (2017). Cross-modal representation of spoken and written word meaning in left pars triangularis. NeuroImage. 150. 292–307. 38 indexed citations
13.
Verheyen, Steven, et al.. (2015). Predicting lexical norms using a word association corpus. Lirias (KU Leuven). 2463–2468. 8 indexed citations
14.
Deyne, Simon De, Steven Verheyen, Amy Perfors, & Danielle Navarro. (2015). Evidence for widespread thematic structure in the mental lexicon. eScholarship (California Digital Library). 518–523. 4 indexed citations
15.
Bruffaerts, Rose, Sophie De Grauwe, Vincent Thijs, et al.. (2014). Noun and knowledge retrieval for biological and non-biological entities following right occipitotemporal lesions. Neuropsychologia. 62. 163–174. 8 indexed citations
16.
Deyne, Simon De, Danielle Navarro, Amy Perfors, & Gert Storms. (2012). Strong structure in weak semantic similarity: a graph based account. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 34(34). 8 indexed citations
17.
Deyne, Simon De, Wouter Voorspoels, Steven Verheyen, Danielle Navarro, & Gert Storms. (2011). Graded structure in adjective categories. eScholarship (California Digital Library). 33(33). 249–254. 4 indexed citations
18.
Deyne, Simon De, Yves Peirsman, & Gert Storms. (2009). Sources of Semantic Similarity. Lirias (KU Leuven). 31(31). 1834–1839. 11 indexed citations
19.
Peirsman, Yves, Simon De Deyne, Kris Heylen, & Dirk Geeraerts. (2008). The Construction and Evaluation of Word Space Models. Language Resources and Evaluation. 1 indexed citations
20.
Deyne, Simon De. (2006). Proximity in Semantic Vector Space.. Lirias (KU Leuven). 3 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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