Daniel Algom

6.1k citations
127 papers · 4.3k · h-index 36

Impact in

Papers in

Daniel Algom

124 papers receiving 4.1k citations

Peers

Daniel Algom
Comparison fields: 5 of 147
  • Cognitive Neuroscience 2.5k
  • General Decision Sciences 246
  • Experimental and Cognitive Psychology 1.4k
  • Applied Psychology 343
  • Statistics and Probability 517
Replace Richard A. Block with:
Richard A. Block United States
Lorraine G. Allan Canada
Ruud Wetzels Netherlands
A. W. Logue United States
Yuejia Luo China
Philip M. Merikle Canada
Jane E. Raymond United Kingdom
Ruth Kimchi Israel
Juan Lupiáñez Spain
Werner Sommer Germany
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Citations per field
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Richard A. Block · 1×
Citations per year

Countries citing papers authored by Daniel Algom

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Algom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Algom, 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 Daniel Algom Line = papers co-authored together Daniel Algom links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 127 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004428
2 2003274
3 2003266
4 2007232
5 2009167
6 1996135
7 199199
8 199996
9 200094
10 198493
11 198587
12 198583
13 200282
14 198477
15 198166
16 199066
17 201664
18 200064
19 201759
20 199456

About Daniel Algom

Daniel Algom is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology, Statistics and Probability, Developmental and Educational Psychology and Social Psychology, having authored 127 papers that have together received 4.3k indexed citations. Recurring topics across this work include Neural and Behavioral Psychology Studies (35 papers), Visual perception and processing mechanisms (27 papers), Cognitive and developmental aspects of mathematical skills (25 papers), Multisensory perception and integration (24 papers), Neuroscience and Music Perception (14 papers), Hearing Loss and Rehabilitation (13 papers), Mathematics Education and Teaching Techniques (9 papers) and Child and Animal Learning Development (9 papers). The work is most often cited by research in Cognitive Neuroscience (2.5k citations), General Decision Sciences (246 citations), Experimental and Cognitive Psychology (1.4k citations), Applied Psychology (343 citations) and Statistics and Probability (517 citations). Daniel Algom has collaborated with scholars based in Israel, United States and Canada. Frequent co-authors include Eran Chajut, Ainat Pansky, Robert D. Melara, Lawrence E. Marks, Yaacov Trope, Yuval Wolf, Daniel Fitousi, William S. Cain, Elinor Amit and Yaniv Mama. Their work appears in journals such as Journal of Experimental Psychology Human Perception & Performance, Journal of Experimental Psychology General, Memory & Cognition, Journal of Experimental Psychology Learning Memory and Cognition and Cognition & Emotion.

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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