Algorithmic Game Theory: Computing in Games
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doi.org/w89380421 →Countries where authors are citing Algorithmic Game Theory: Computing in Games
This map shows the geographic impact of Algorithmic Game Theory: Computing in Games. 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 Algorithmic Game Theory: Computing in Games with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Algorithmic Game Theory: Computing in Games more than expected).
Fields of papers citing Algorithmic Game Theory: Computing in Games
This network shows the impact of Algorithmic Game Theory: Computing in Games. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Algorithmic Game Theory: Computing in Games.
About Algorithmic Game Theory: Computing in Games
This paper, published in 2007, received 762 indexed citations . Written by Noam Nisan, Tim Roughgarden, Éva Tardos and Vijay V. Vazirani covering the research area of Computational Theory and Mathematics and Artificial Intelligence. It is primarily cited by scholars working on Management Science and Operations Research (426 citations), Computer Networks and Communications (284 citations), Economics and Econometrics (163 citations), Electrical and Electronic Engineering (125 citations) and Artificial Intelligence (124 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.
This paper is also available at doi.org/w89380421.