David Chavalarias

1.0k citations
26 papers · 549 · 1 hit paper · h-index 9

Impact in

Papers in

David Chavalarias

24 papers receiving 535 citations

David Chavalarias's Hit Papers

Evolution of Reporting P Values in the Biomedical Literature, 1990-2015 2016 · 217 citations
2170+3+6Years since publication50100150200

Peers

David Chavalarias
Comparison fields: 5 of 147
  • Statistics, Probability and Uncertainty 179
  • Statistics and Probability 65
  • Communication 45
  • Statistical and Nonlinear Physics 62
  • History and Philosophy of Science 17
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Isola Ajiferuke Canada
Nan Lin China
Jeff Gill United States
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Ryan Chute United States
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Rosa Rodríguez‐Sánchez Spain
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Countries citing papers authored by David Chavalarias

Since Specialization
Citations

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

Fields of papers citing papers by David Chavalarias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside David Chavalarias, 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 David Chavalarias Line = papers co-authored together David Chavalarias links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Evolution of Reporting P Values in the Biomedical Literature, 1990-2015
Hit paper breakdown →
2016217
2 201377
3 201067
4 201847
5 202024
6 200822
7 201615
8 201511
9 20238
10 20218
11 20208
12 20087
13 20197
14 20216
15 20166
16 20244
17
Streams of Media Issues, Monitoring World Food Security
20113
18 20142
19 20092
20 20192

About David Chavalarias

David Chavalarias is a scholar working on Statistical and Nonlinear Physics, Sociology and Political Science, Molecular Biology, Statistics, Probability and Uncertainty and Communication, having authored 26 papers that have together received 549 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (8 papers), scientometrics and bibliometrics research (5 papers), Opinion Dynamics and Social Influence (5 papers), Social Media and Politics (3 papers), Diverse multidisciplinary academic research (3 papers), Advanced Text Analysis Techniques (2 papers), Complex Systems and Time Series Analysis (2 papers) and Biomedical Text Mining and Ontologies (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (179 citations), Statistics and Probability (65 citations), Communication (45 citations), Statistical and Nonlinear Physics (62 citations) and History and Philosophy of Science (17 citations). David Chavalarias has collaborated with scholars based in France, United States and Italy. Frequent co-authors include John P. A. Ioannidis, Joshua D. Wallach, Jean‐Philippe Cointet, Masaru Mizoguchi, Cyrille Bertelle, Franck Varenne, Francis Chateauraynaud, Nicolas Brodu, Arnaud Banos and Pablo Jensen. Their work appears in journals such as Scientometrics, Journal of Clinical Epidemiology, PLoS ONE, JAMA and Scientific Reports.

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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