Daniel Yurovsky

3.3k total citations · 3 hit papers
47 papers, 1.6k citations indexed

About

Daniel Yurovsky is a scholar working on Developmental and Educational Psychology, Artificial Intelligence and Cultural Studies. According to data from OpenAlex, Daniel Yurovsky has authored 47 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Developmental and Educational Psychology, 14 papers in Artificial Intelligence and 12 papers in Cultural Studies. Recurrent topics in Daniel Yurovsky's work include Language Development and Disorders (26 papers), Child and Animal Learning Development (23 papers) and Reading and Literacy Development (13 papers). Daniel Yurovsky is often cited by papers focused on Language Development and Disorders (26 papers), Child and Animal Learning Development (23 papers) and Reading and Literacy Development (13 papers). Daniel Yurovsky collaborates with scholars based in United States, Netherlands and Canada. Daniel Yurovsky's co-authors include Michael C. Frank, Mika Braginsky, Virginia A. Marchman, Chen Yu, Linda B. Smith, Kyle MacDonald, Molly Lewis, Alexandra Horowitz, Clara C. Levelt and Jessica Sullivan and has published in prestigious journals such as PLoS ONE, Child Development and Psychological Science.

In The Last Decade

Daniel Yurovsky

42 papers receiving 1.5k citations

Hit Papers

Wordbank: an open repository for developmental vocabulary... 2016 2026 2019 2022 2016 2017 2021 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Yurovsky United States 21 1.2k 373 267 257 130 47 1.6k
Jessica S. Horst United Kingdom 25 1.6k 1.3× 601 1.6× 325 1.2× 190 0.7× 307 2.4× 47 2.1k
Elika Bergelson United States 20 1.6k 1.3× 400 1.1× 504 1.9× 200 0.8× 228 1.8× 63 2.0k
D. Geoffrey Hall Canada 23 1.4k 1.1× 327 0.9× 356 1.3× 147 0.6× 94 0.7× 58 1.6k
Hugh Rabagliati United Kingdom 19 815 0.7× 745 2.0× 347 1.3× 164 0.6× 54 0.4× 53 1.3k
Amanda Seidl United States 19 988 0.8× 254 0.7× 576 2.2× 194 0.8× 171 1.3× 43 1.3k
Kathryn Hirsh‐Pasek United States 16 1.3k 1.0× 352 0.9× 263 1.0× 86 0.3× 444 3.4× 22 1.7k
Ayli̇n C. Küntay Türkiye 20 743 0.6× 358 1.0× 245 0.9× 196 0.8× 200 1.5× 94 1.3k
Julian Jara‐Ettinger United States 17 747 0.6× 458 1.2× 310 1.2× 253 1.0× 186 1.4× 84 1.5k
Hans Stadthagen-González United States 17 907 0.7× 866 2.3× 525 2.0× 391 1.5× 100 0.8× 26 1.7k
Arnaud Rey France 22 898 0.7× 718 1.9× 313 1.2× 181 0.7× 107 0.8× 61 1.4k

Countries citing papers authored by Daniel Yurovsky

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Yurovsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Yurovsky

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Yurovsky. A scholar is included among the top collaborators of Daniel Yurovsky 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 Daniel Yurovsky. Daniel Yurovsky 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.
Tarr, Michael J., et al.. (2025). Quantifying the roles of visual, linguistic, and visual-linguistic complexity in noun and verb acquisition. PLoS ONE. 20(5). e0321973–e0321973.
2.
Yurovsky, Daniel, et al.. (2024). Of Mouses and Mans: A Test of Errorless Versus Error‐Based Learning in Children. Cognitive Science. 48(11). e70006–e70006.
3.
Zettersten, Martin, Mika Braginsky, George Kachergis, et al.. (2021). Peekbank: Exploring children's word recognition through an open, large-scale repository for developmental eye-tracking data. eScholarship (California Digital Library). 6 indexed citations
4.
Frank, Michael C., Mika Braginsky, Daniel Yurovsky, & Virginia A. Marchman. (2021). Variability and Consistency in Early Language Learning. The MIT Press eBooks. 121 indexed citations breakdown →
5.
Meylan, Stephan C., et al.. (2019). childes-db: A flexible and reproducible interface to the child language data exchange system. Behavior Research Methods. 51(4). 1928–1941. 52 indexed citations
6.
Yurovsky, Daniel, et al.. (2018). Children gesture when speech is slow to come.. Cognitive Science.
7.
MacDonald, Kyle, Daniel Yurovsky, & Michael C. Frank. (2017). Social cues modulate the representations underlying cross-situational learning. Cognitive Psychology. 94. 67–84. 16 indexed citations
8.
Braginsky, Mika, et al.. (2016). From uh-oh to tomorrow: Predicting age of acquisition for early words across languages.. Cognitive Science. 24 indexed citations
9.
Benitez, Viridiana L., Daniel Yurovsky, & Linda B. Smith. (2016). Competition between multiple words for a referent in cross-situational word learning. Journal of Memory and Language. 90. 31–48. 25 indexed citations
10.
Yurovsky, Daniel, Gabriel Doyle, & Michael C. Frank. (2016). Linguistic input is tuned to children's developmental level.. Cognitive Science. 16 indexed citations
11.
Schneider, Rose M., et al.. (2015). Large-scale investigations of variability in children's first words.. Cognitive Science. 15 indexed citations
12.
Braginsky, Mika, Daniel Yurovsky, Virginia A. Marchman, & Michael C. Frank. (2015). Developmental Changes in the Relationship Between Grammar and the Lexicon.. Cognitive Science. 14 indexed citations
13.
Yurovsky, Daniel, Anna Wade, & Michael C. Frank. (2013). Online Processing of Speech and Social Information in Early Word Learning. Cognitive Science. 35(35). 5 indexed citations
14.
Frank, Michael C., et al.. (2013). Developmental and postural changes in children's visual access to faces.. Cognitive Science. 35(35). 21 indexed citations
15.
Yurovsky, Daniel, et al.. (2013). The role of partial knowledge in statistical word learning. Psychonomic Bulletin & Review. 21(1). 1–22. 63 indexed citations
16.
Yurovsky, Daniel, Ricardo A. H. Bion, Linda B. Smith, & Anne Fernald. (2012). Mutual Exclusivity and Vocabulary Development. Cognitive Science. 34(34). 2 indexed citations
17.
Yurovsky, Daniel, Linda B. Smith, & Chen Yu. (2012). Does Statistical Word Learning Scale? It’s a Matter of Perspective. Cognitive Science. 34(34). 3 indexed citations
18.
Yurovsky, Daniel, et al.. (2012). Quantitative Linking Hypotheses for Infant Eye Movements. PLoS ONE. 7(10). e47419–e47419. 6 indexed citations
19.
Yurovsky, Daniel, Chen Yu, & Linda B. Smith. (2012). Statistical Speech Segmentation and Word Learning in Parallel: Scaffolding from Child-Directed Speech. Frontiers in Psychology. 3. 374–374. 33 indexed citations
20.
Yurovsky, Daniel & Chen Yu. (2008). Mutual Exclusivity in Cross-Situational Statistical Learning. eScholarship (California Digital Library). 23 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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