Matthew Piva

14 total papers · 550 total citations
12 papers, 373 citations indexed

About

Matthew Piva is a scholar working on Social Psychology, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Matthew Piva has authored 12 papers receiving a total of 373 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Social Psychology, 4 papers in Cognitive Neuroscience and 3 papers in Molecular Biology. Recurrent topics in Matthew Piva's work include Neuroendocrine regulation and behavior (5 papers), Attachment and Relationship Dynamics (3 papers) and Evolutionary Psychology and Human Behavior (3 papers). Matthew Piva is often cited by papers focused on Neuroendocrine regulation and behavior (5 papers), Attachment and Relationship Dynamics (3 papers) and Evolutionary Psychology and Human Behavior (3 papers). Matthew Piva collaborates with scholars based in United States, Canada and Russia. Matthew Piva's co-authors include Steve W. C. Chang, Olga Dal Monte, Evelyn K. Lambe, Xian Zhang, Ifat Levy, Joy Hirsch, Amrita R. Nair, Craig D. C. Bailey, J. Adam Noah and Avram J. Holmes and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Trends in Cognitive Sciences and Journal of Neurophysiology.

In The Last Decade

Matthew Piva

12 papers receiving 369 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Matthew Piva 173 146 65 54 45 12 373
Ryan T. Johnson 175 1.0× 109 0.7× 60 0.9× 41 0.8× 49 1.1× 11 440
Fred D. Sheffield 82 0.5× 132 0.9× 53 0.8× 18 0.3× 73 1.6× 8 425
Rongfeng K. Hu 143 0.8× 250 1.7× 46 0.7× 50 0.9× 109 2.4× 12 394
Catherine Marchaland 95 0.5× 60 0.4× 84 1.3× 68 1.3× 35 0.8× 11 416
E Fonberg 128 0.7× 140 1.0× 30 0.5× 18 0.3× 83 1.8× 20 373
Anthony M. Dodge 111 0.6× 258 1.8× 51 0.8× 43 0.8× 153 3.4× 8 436
Vickie R. Luttrell 58 0.3× 107 0.7× 69 1.1× 18 0.3× 29 0.6× 6 333
Nastacia L. Goodwin 51 0.3× 200 1.4× 80 1.2× 33 0.6× 58 1.3× 15 343
Cannie Stark-Adamec 166 1.0× 174 1.2× 29 0.4× 44 0.8× 174 3.9× 23 421
Dana Rubi Levy 207 1.2× 155 1.1× 46 0.7× 49 0.9× 109 2.4× 8 428

Countries citing papers authored by Matthew Piva

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Piva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Piva

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Piva. A scholar is included among the top collaborators of Matthew Piva 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 Matthew Piva. Matthew Piva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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