Graph evolution
Impact in
Classified as
In The Last Decade
doi.org/10.1145/1217299.1217301 →Countries where authors are citing Graph evolution
This map shows the geographic impact of Graph evolution. 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 Graph evolution with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Graph evolution more than expected).
Fields of papers citing Graph evolution
This network shows the impact of Graph evolution. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Graph evolution.
About Graph evolution
This paper, published in 2007, received 1.9k indexed citations . Written by Jure Leskovec, Jon Kleinberg and Christos Faloutsos covering the research area of Sociology and Political Science and Statistical and Nonlinear Physics. It is primarily cited by scholars working on Statistical and Nonlinear Physics (1.4k citations), Artificial Intelligence (599 citations), Computer Networks and Communications (433 citations), Sociology and Political Science (211 citations) and Computer Vision and Pattern Recognition (210 citations). Published in ACM Transactions on Knowledge Discovery from Data.
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/10.1145/1217299.1217301.