Iván Garibay

1.3k total citations
49 papers, 390 citations indexed

About

Iván Garibay is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Sociology and Political Science. According to data from OpenAlex, Iván Garibay has authored 49 papers receiving a total of 390 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 14 papers in Statistical and Nonlinear Physics and 9 papers in Sociology and Political Science. Recurrent topics in Iván Garibay's work include Complex Network Analysis Techniques (14 papers), Evolutionary Algorithms and Applications (11 papers) and Opinion Dynamics and Social Influence (10 papers). Iván Garibay is often cited by papers focused on Complex Network Analysis Techniques (14 papers), Evolutionary Algorithms and Applications (11 papers) and Opinion Dynamics and Social Influence (10 papers). Iván Garibay collaborates with scholars based in United States, Jordan and Peru. Iván Garibay's co-authors include Annie S. Wu, Alexander V. Mantzaris, Cameron M. Ford, Stephen A. Sivo, Özlem Özmen Garibay, William Rand, Gita Sukthankar, Karla Badillo-Urquiola, Erez Hatna and Joshua M. Epstein and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Cleaner Production.

In The Last Decade

Iván Garibay

46 papers receiving 365 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Iván Garibay United States 10 82 82 76 71 44 49 390
Tatiana Khvatova Russia 12 33 0.4× 102 1.2× 36 0.5× 47 0.7× 23 0.5× 34 424
David Askay United States 8 31 0.4× 86 1.0× 102 1.3× 46 0.6× 14 0.3× 16 463
Francisco José Muñoz-Fernández Spain 6 47 0.6× 53 0.6× 59 0.8× 28 0.4× 67 1.5× 9 555
Alisa Kongthon Thailand 12 41 0.5× 106 1.3× 137 1.8× 57 0.8× 34 0.8× 33 519
Hauke Fuehres Germany 5 147 1.8× 103 1.3× 144 1.9× 18 0.3× 79 1.8× 5 477
Renger E. de Bruin Netherlands 10 80 1.0× 48 0.6× 46 0.6× 24 0.3× 40 0.9× 12 715
Robert R. Braam Netherlands 9 52 0.6× 54 0.7× 163 2.1× 50 0.7× 110 2.5× 9 614
Lele Kang China 12 120 1.5× 133 1.6× 29 0.4× 27 0.4× 7 0.2× 36 392
Jingqin Su China 10 73 0.9× 62 0.8× 16 0.2× 96 1.4× 22 0.5× 29 476
Elise Bassecoulard Morocco 14 99 1.2× 52 0.6× 79 1.0× 84 1.2× 139 3.2× 16 854

Countries citing papers authored by Iván Garibay

Since Specialization
Citations

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

Fields of papers citing papers by Iván Garibay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iván Garibay

This figure shows the co-authorship network connecting the top 25 collaborators of Iván Garibay. A scholar is included among the top collaborators of Iván Garibay 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 Iván Garibay. Iván Garibay is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Garibay, Iván, et al.. (2024). Accelerating green growth: The effect of technological innovation on production capabilities spillovers in developing economies. Journal of Cleaner Production. 482. 144159–144159. 5 indexed citations
2.
Rand, William, et al.. (2024). Comparing Social Media Communities using Functional Data Analysis. Proceedings of the ... Annual Hawaii International Conference on System Sciences. 2024. 4162–4171.
3.
Hatna, Erez, et al.. (2023). Generating Mixed Patterns of Residential Segregation: An Evolutionary Approach. Journal of Artificial Societies and Social Simulation. 26(2). 5 indexed citations
4.
Epstein, Joshua M., et al.. (2023). Special Section on "Inverse Generative Social Science": Guest Editors’ Statement. Journal of Artificial Societies and Social Simulation. 26(2). 1 indexed citations
5.
Miller, Bruce L., et al.. (2023). Network Structure Can Amplify Innovation Adoption and Polarization in Group-Structured Populations with Outgroup Aversion. Journal of Artificial Societies and Social Simulation. 26(4). 1 indexed citations
6.
Garibay, Iván, et al.. (2023). A survey on sign language literature. SHILAP Revista de lepidopterología. 14. 100504–100504. 10 indexed citations
7.
8.
Rand, William, et al.. (2021). Inferring mechanisms of response prioritization on social media under information overload. Scientific Reports. 11(1). 1346–1346. 9 indexed citations
9.
Garibay, Iván, et al.. (2021). Controversial information spreads faster and further than non-controversial information in Reddit. Journal of Computational Social Science. 5(1). 111–122. 16 indexed citations
10.
Garibay, Iván, et al.. (2020). Evolutionary model discovery of causal factors behind the socio-agricultural behavior of the Ancestral Pueblo. PLoS ONE. 15(12). e0239922–e0239922. 14 indexed citations
11.
Mantzaris, Alexander V., et al.. (2020). Modeling Disinformation and the Effort to Counter It: A Cautionary Tale of When the Treatment Can Be Worse Than the Disease. Adaptive Agents and Multi-Agents Systems. 1975–1977. 3 indexed citations
12.
Sukthankar, Gita, et al.. (2020). Modeling social coding dynamics with sampled historical data. 16. 100070–100070. 6 indexed citations
13.
Garibay, Iván, et al.. (2019). VizTract: Visualization of Complex Social Networks for Easy User Perception. Big Data and Cognitive Computing. 3(1). 17–17. 7 indexed citations
14.
Garibay, Iván, et al.. (2019). Polarization in social media assists influencers to become more influential: analysis and two inoculation strategies. Scientific Reports. 9(1). 18592–18592. 28 indexed citations
15.
Sukthankar, Gita, et al.. (2018). A Cross-Repository Model For Predicting Popularity In Github. Journal of International Crisis and Risk Communication Research. 2 indexed citations
16.
Garibay, Iván, et al.. (2017). Agent-Based Modeling For Causal Exploration Of Social Systems. Journal of International Crisis and Risk Communication Research. 1 indexed citations
17.
Garibay, Iván, et al.. (2017). Alternate social theory discovery using genetic programming. Proceedings of the Genetic and Evolutionary Computation Conference. 115–122. 8 indexed citations
18.
Öner, Mualla, Iván Garibay, & Annie S. Wu. (2006). Mating networks in steady state genetic algorithms are scale free. Journal of International Crisis and Risk Communication Research. 1423–1424. 2 indexed citations
19.
Wu, Annie S. & Iván Garibay. (2004). Intelligent Automated Control of Life Support Systems Using Proportional Representations. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 34(3). 1423–1434. 9 indexed citations
20.
Wu, Annie S. & Iván Garibay. (2002). The Proportional Genetic Algorithm Representation. Genetic and Evolutionary Computation Conference. 703–703. 1 indexed citations

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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