Amir Ghasemian

15 papers and 340 indexed citations i.

About

Amir Ghasemian is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Sociology and Political Science. According to data from OpenAlex, Amir Ghasemian has authored 15 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 7 papers in Statistical and Nonlinear Physics and 5 papers in Sociology and Political Science. Recurrent topics in Amir Ghasemian’s work include Complex Network Analysis Techniques (7 papers), Social Media and Politics (5 papers) and Advanced Graph Neural Networks (3 papers). Amir Ghasemian is often cited by papers focused on Complex Network Analysis Techniques (7 papers), Social Media and Politics (5 papers) and Advanced Graph Neural Networks (3 papers). Amir Ghasemian collaborates with scholars based in United States, Iran and South Korea. Amir Ghasemian's co-authors include Aaron Clauset, Homa Hosseinmardi, Homa Hosseinmardi, Aram Galstyan, Duncan J. Watts, Edoardo M. Airoldi, Markus Möbius, David Rothschild, Pan Zhang and Leto Peel and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

In The Last Decade

Co-authorship network of co-authors of Amir Ghasemian i

Fields of papers citing papers by Amir Ghasemian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Amir Ghasemian

Since Specialization
Citations

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

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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2025