M. Canan

19 papers receiving 70 citations

Peers

M. Canan
Comparison fields: 5 of 36
  • General Decision Sciences 8
  • Management Science and Operations Research 12
  • Computer Science Applications 5
  • Social Psychology 17
  • Information Systems 18
Replace Marco Antonio Sobrevilla Cabezudo with:
Marco Antonio Sobrevilla Cabezudo Brazil
Ewa Andrejczuk Spain
Lingjia Deng United States
Alex Marin United States
Ivan Sekulić Switzerland
Mohammad Abid Khan Pakistan
Lina Maria Rojas-Barahona United Kingdom
Stefanos Angelidis United Kingdom
Tomáš Brychcín Czechia
Clara Vania United States
M. Canan relative to Marco Antonio Sobrevilla Cabezudo Brazil Marco Antonio Sobrevilla Cabezudo's profile →
Citations per field
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Marco Antonio Sobrevilla Cabezudo · 1×
Citations per year

Countries citing papers authored by M. Canan

Since Specialization
Citations

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

Fields of papers citing papers by M. Canan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside M. Canan, 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 M. Canan Line = papers co-authored together M. Canan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202016
2 202213
3 20237
4 20196
5 20165
6 20174
7 20154
8 20223
9 20223
10 20213
11 20252
12 20212
13 20232
14
Countering Disinformation Propaganda: Reverse Engineering the Experimental Implicit Learning Paradigm
20201
15 20161
16 20231
17 20221
18 20221
19 20241
20 20181

About M. Canan

M. Canan is a scholar working on Management Science and Operations Research, General Decision Sciences, Artificial Intelligence, Social Psychology and Statistical and Nonlinear Physics, having authored 23 papers that have together received 77 indexed citations. Recurring topics across this work include Cognitive Science and Mapping (8 papers), Complex Systems and Decision Making (7 papers), Decision-Making and Behavioral Economics (4 papers), Quantum Mechanics and Applications (3 papers), Image and Object Detection Techniques (3 papers), Team Dynamics and Performance (3 papers), Human-Automation Interaction and Safety (3 papers) and Bayesian Modeling and Causal Inference (2 papers). The work is most often cited by research in General Decision Sciences (8 citations), Management Science and Operations Research (12 citations), Computer Science Applications (5 citations), Social Psychology (17 citations) and Information Systems (18 citations). M. Canan has collaborated with scholars based in United States and Ghana. Frequent co-authors include Andres Sousa‐Poza, Mustafa Demir, Cesar Ariel Pinto, Jiang Li, Michael K. McShane, Mohammad Shahab Uddin and Anthony Dean. Their work appears in journals such as The Geneva Papers on Risk and Insurance Issues and Practice, Journal of the Association for Information Systems, Computational and Mathematical Organization Theory, IEEE Transactions on Human-Machine Systems and Entropy.

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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