Maud Besançon

125 total papers · 1.6k total citations
36 papers, 874 citations indexed

About

Maud Besançon is a scholar working on Experimental and Cognitive Psychology, Cognitive Neuroscience and Developmental and Educational Psychology. According to data from OpenAlex, Maud Besançon has authored 36 papers receiving a total of 874 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Experimental and Cognitive Psychology, 9 papers in Cognitive Neuroscience and 7 papers in Developmental and Educational Psychology. Recurrent topics in Maud Besançon's work include Creativity in Education and Neuroscience (25 papers), Education, Achievement, and Giftedness (8 papers) and Neuroscience, Education and Cognitive Function (8 papers). Maud Besançon is often cited by papers focused on Creativity in Education and Neuroscience (25 papers), Education, Achievement, and Giftedness (8 papers) and Neuroscience, Education and Cognitive Function (8 papers). Maud Besançon collaborates with scholars based in France, United States and Belgium. Maud Besançon's co-authors include Todd Lubart, Baptiste Barbot, Franck Zenasni, Corentin Gonthier, Rébecca Shankland, Fabien Fenouillet, Thalia R. Goldstein, Jacques‐Henri Guignard, Jacques Grégoire and Uğur Sak and has published in prestigious journals such as Frontiers in Psychology, Intelligence and Learning and Individual Differences.

In The Last Decade

Maud Besançon

34 papers receiving 811 citations

Author Peers

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

Author						Papers	Cites
Maud Besançon	647	219	195	174	154	36	874
Aleksandra Gajda	657 1.0×	238 1.1×	199 1.0×	188 1.1×	144 0.9×	23	969
Jacek Gralewski	805 1.2×	239 1.1×	168 0.9×	242 1.4×	119 0.8×	23	1.0k
Gerard J. Puccio	601 0.9×	98 0.4×	124 0.6×	198 1.1×	124 0.8×	30	866
Lisa DaVia Rubenstein	443 0.7×	83 0.4×	354 1.8×	192 1.1×	194 1.3×	45	823
Jen Katz‐Buonincontro	362 0.6×	89 0.4×	306 1.6×	104 0.6×	144 0.9×	41	844
John Curtis Gowan	433 0.7×	109 0.5×	189 1.0×	124 0.7×	113 0.7×	58	731
Ahmed M. Abdulla Alabbasi	472 0.7×	164 0.7×	101 0.5×	182 1.0×	106 0.7×	45	753
Edward Nȩcka	567 0.9×	328 1.5×	117 0.6×	141 0.8×	178 1.2×	49	925
Elisabeth Rudowicz	504 0.8×	92 0.4×	116 0.6×	229 1.3×	70 0.5×	21	702
Dan Davies	370 0.6×	93 0.4×	488 2.5×	110 0.6×	177 1.1×	62	965

Countries citing papers authored by Maud Besançon

Since Specialization

Citations

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

Fields of papers citing papers by Maud Besançon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maud Besançon

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