Computer Science Applications

155.9k papers and 2.0M indexed citations i.

About

155.9k papers covering Computer Science Applications have received a total of 2.0M indexed citations since 1950. Papers on subfields are most often about the specific topic of Online Learning and Analytics, E-Learning and Knowledge Management and Teaching and Learning Programming and also cover the fields of Information Systems, Education and Developmental and Educational Psychology. Papers citing papers on subfields are usually about Education, Information Systems and Artificial Intelligence. Some of the most active scholars covering Computer Science Applications are Eric von Hippel, James Paul Gee, Morten T. Hansen, Jesse Chandler, Gabriele Paolacci, John Seely Brown, Henry Chesbrough, Karim R. Lakhani, Panagiotis G. Ipeirotis and D. Randy Garrison.

In The Last Decade

Fields of papers citing papers about Computer Science Applications

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers covering Computer Science Applications. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers covering Computer Science Applications.

Countries where authors publish papers about Computer Science Applications

Since Specialization

Citations

This map shows the geographic impact of research in Computer Science Applications. 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 papers about Computer Science Applications with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Computer Science Applications 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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