Stephan C. Meylan

546 citations
16 papers · 202 · h-index 7

Impact in

Papers in

Stephan C. Meylan

14 papers receiving 191 citations

Peers

Stephan C. Meylan
Comparison fields: 5 of 35
  • Developmental and Educational Psychology 129
  • Cultural Studies 46
  • Experimental and Cognitive Psychology 36
  • Artificial Intelligence 77
  • Language and Linguistics 22
Replace Rebecca Louise Ann Frost with:
Rebecca Louise Ann Frost United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Stephan C. Meylan

Since Specialization
Citations

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

Fields of papers citing papers by Stephan C. Meylan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephan C. Meylan. 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 Stephan C. Meylan. The network helps show where Stephan C. Meylan may publish in the future.

Co-authors

The 23 scholars most cited alongside Stephan C. Meylan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stephan C. Meylan Line = papers co-authored together Stephan C. Meylan links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 201954
2 201344
3
Evaluating Vector-Space Models of Word Representation, or, The Unreasonable Effectiveness of Counting Words Near Other Words.
201728
4 201722
5 202113
6 202111
7
The Divergent Lexicon: Lexical Overlap Decreases With Age in a Large Corpus of Conversational Speech
20147
8 20216
9
Modeling online word segmentation performance in structured artificial languages
20123
10 20213
11 20213
12 20242
13 20232
14
Zipfian word frequencies support statistical word segmentation
20112
15
Representing linguistic knowledge with probabilistic models
20181
16
Modeling the Development of Determiner Productivity in Children's Early Speech
20131

About Stephan C. Meylan

Stephan C. Meylan is a scholar working on Developmental and Educational Psychology, Artificial Intelligence, Cultural Studies, Experimental and Cognitive Psychology and Molecular Biology, having authored 16 papers that have together received 202 indexed citations. Recurring topics across this work include Language Development and Disorders (9 papers), Speech and dialogue systems (7 papers), Natural Language Processing Techniques (6 papers), Language and cultural evolution (6 papers), Reading and Literacy Development (4 papers), Phonetics and Phonology Research (3 papers), Topic Modeling (2 papers) and Child and Animal Learning Development (2 papers). The work is most often cited by research in Developmental and Educational Psychology (129 citations), Cultural Studies (46 citations), Experimental and Cognitive Psychology (36 citations), Artificial Intelligence (77 citations) and Language and Linguistics (22 citations). Stephan C. Meylan has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Michael C. Frank, Thomas L. Griffiths, Chigusa Kurumada, Mika Braginsky, Daniel Yurovsky, Kyle MacDonald, Aida Nematzadeh, Elika Bergelson, Roger Lévy and Brandon Roy. Their work appears in journals such as Cognitive Science, Cognition, Annual Review of Linguistics, Psychological Science and Nature Human Behaviour.

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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