Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Wordbank: an open repository for developmental vocabulary data
2016390 citationsMichael C. Frank, Mika Braginsky et al.profile →
A Collaborative Approach to Infant Research: Promoting Reproducibility, Best Practices, and Theory‐Building
2017175 citationsMichael C. Frank, Daniel Yurovsky et al.profile →
Variability and Consistency in Early Language Learning
2021121 citationsMichael C. Frank, Mika Braginsky et al.The MIT Press eBooksprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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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).
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.
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 →
Braginsky, Mika, et al.. (2016). From uh-oh to tomorrow: Predicting age of acquisition for early words across languages.. Cognitive Science.24 indexed citations
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
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
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.