Igor Dolgov

1.1k citations
59 papers · 699 · h-index 16

Impact in

Papers in

    • Human-Automation Interaction and Safety 17
    • Team Dynamics and Performance 7
    • Visual perception and processing mechanisms 9
    • Neural and Behavioral Psychology Studies 6

Igor Dolgov

57 papers receiving 653 citations

Peers

Igor Dolgov
Comparison fields: 5 of 103
  • Human-Computer Interaction 168
  • Communication 86
  • Cognitive Neuroscience 170
  • Developmental and Educational Psychology 102
  • Social Psychology 162
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Citations per year

Countries citing papers authored by Igor Dolgov

Since Specialization
Citations

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

Fields of papers citing papers by Igor Dolgov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201793
2 201457
3 200836
4 201228
5 201328
6 201728
7 201725
8 201324
9 200921
10 202019
11 201319
12 201819
13 202118
14 201818
15 201817
16 201916
17 200515
18 201715
19 202115
20 201812

About Igor Dolgov

Igor Dolgov is a scholar working on Social Psychology, Cognitive Neuroscience, Human-Computer Interaction, Computer Vision and Pattern Recognition and Sociology and Political Science, having authored 59 papers that have together received 699 indexed citations. Recurring topics across this work include Human-Automation Interaction and Safety (17 papers), Visual perception and processing mechanisms (9 papers), Team Dynamics and Performance (7 papers), Neural and Behavioral Psychology Studies (6 papers), Virtual Reality Applications and Impacts (6 papers), Air Traffic Management and Optimization (5 papers), Innovative Human-Technology Interaction (5 papers) and Augmented Reality Applications (5 papers). The work is most often cited by research in Human-Computer Interaction (168 citations), Communication (86 citations), Cognitive Neuroscience (170 citations), Developmental and Educational Psychology (102 citations) and Social Psychology (162 citations). Igor Dolgov has collaborated with scholars based in United States, Canada and Saudi Arabia. Frequent co-authors include Jeremy Schwark, Sultan A. Alharthi, Joshua Sandry, Ivan B. Dylko, William Hoffman, María D. Molina, Phoebe O. Toups Dugas, Justin A. MacDonald, Michael K. McBeath and Dennis M. Shaffer. Their work appears in journals such as Perception, Journal of Vision, Attention Perception & Psychophysics, Computers in Human Behavior and ACM Transactions on Computer-Human Interaction.

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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