Matthew Haigh

51 total papers · 1.7k total citations
29 papers, 333 citations indexed

About

Matthew Haigh is a scholar working on Experimental and Cognitive Psychology, Developmental and Educational Psychology and Cognitive Neuroscience. According to data from OpenAlex, Matthew Haigh has authored 29 papers receiving a total of 333 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Experimental and Cognitive Psychology, 8 papers in Developmental and Educational Psychology and 7 papers in Cognitive Neuroscience. Recurrent topics in Matthew Haigh's work include Language, Metaphor, and Cognition (9 papers), Language, Discourse, Communication Strategies (7 papers) and Child and Animal Learning Development (6 papers). Matthew Haigh is often cited by papers focused on Language, Metaphor, and Cognition (9 papers), Language, Discourse, Communication Strategies (7 papers) and Child and Animal Learning Development (6 papers). Matthew Haigh collaborates with scholars based in United Kingdom, France and Hungary. Matthew Haigh's co-authors include Andrew Stewart, Roger T. Webb, Evan Kidd, Jayne Cooper, Navneet Kapur, Sarah Steeg, Keith Waters, Jennifer Ness, Helen Bergen and Keith Hawton and has published in prestigious journals such as PLoS ONE, Journal of Affective Disorders and Journal of Experimental Psychology Learning Memory and Cognition.

In The Last Decade

Matthew Haigh

27 papers receiving 321 citations

Author Peers

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

Author						Papers	Cites
Matthew Haigh	126	96	75	72	57	29	333
Michelle M. Arnold	48 0.4×	77 0.8×	59 0.8×	181 2.5×	15 0.3×	24	341
Ali Teymoori	126 1.0×	136 1.4×	49 0.7×	36 0.5×	21 0.4×	30	395
Philippe Chassy	27 0.2×	80 0.8×	59 0.8×	115 1.6×	13 0.2×	21	393
Yosef Sokol	187 1.5×	112 1.2×	166 2.2×	44 0.6×	8 0.1×	25	384
Christopher Schroth	149 1.2×	79 0.8×	108 1.4×	46 0.6×	16 0.3×	18	324
James J. Hennessy	152 1.2×	86 0.9×	59 0.8×	19 0.3×	7 0.1×	45	389
Paul F. Zelhart	142 1.1×	72 0.8×	66 0.9×	33 0.5×	10 0.2×	32	350
Anneli Jefferson	53 0.4×	75 0.8×	75 1.0×	146 2.0×	3 0.1×	24	375
Alison Pickover	121 1.0×	69 0.7×	55 0.7×	30 0.4×	3 0.1×	25	354
K. Roger Van Horn	79 0.6×	94 1.0×	53 0.7×	51 0.7×	13 0.2×	18	302

Countries citing papers authored by Matthew Haigh

Since Specialization

Citations

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

Fields of papers citing papers by Matthew Haigh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Haigh

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Haigh. A scholar is included among the top collaborators of Matthew Haigh 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 Haigh. Matthew Haigh 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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