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.
Text as Data
2019575 citationsMatthew Gentzkow, Bryan Kelly et al.Journal of Economic Literatureprofile →
Measuring Group Differences in High‐Dimensional Choices: Method and Application to Congressional Speech
2019195 citationsMatthew Gentzkow, Jesse M. Shapiro et al.profile →
Measuring Technological Innovation over the Long Run
2021166 citationsDimitris Papanikolaou, Amit Seru et al.RePEc: Research Papers in Economicsprofile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
citations ·
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This map shows the geographic impact of Matt Taddy'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 Matt Taddy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matt Taddy more than expected).
This network shows the impact of papers produced by Matt Taddy. 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 Matt Taddy. The network helps show where Matt Taddy may publish in the future.
Co-authorship network of co-authors of Matt Taddy
This figure shows the co-authorship network connecting the top 25 collaborators of Matt Taddy.
A scholar is included among the top collaborators of Matt Taddy 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 Matt Taddy. Matt Taddy is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Papanikolaou, Dimitris, et al.. (2021). Measuring Technological Innovation over the Long Run. RePEc: Research Papers in Economics. 3(3). 303–320.166 indexed citations breakdown →
3.
Gentzkow, Matthew, Bryan Kelly, & Matt Taddy. (2019). Text as Data. Journal of Economic Literature. 57(3). 535–574.575 indexed citations breakdown →
Gentzkow, Matthew, Jesse M. Shapiro, & Matt Taddy. (2016). Measuring Polarization in High-Dimensional Data: Method and Application to Congressional Speech. SSRN Electronic Journal.32 indexed citations
10.
Taddy, Matt, Hedibert F. Lopes, & Matt Gardner. (2016). Semi-parametric inference for the means of heavy-tailed distributions. arXiv (Cornell University).1 indexed citations
Carvalho, Carlos M., Hedibert F. Lopes, Nicholas G. Polson, & Matt Taddy. (2010). Particle learning for general mixtures. Bayesian Analysis. 5(4).35 indexed citations
20.
Gray, Genetha A., et al.. (2008). Enhancing Parallel Pattern Search Optimization with a Gaussian Process Oracle.1 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.