Computers in Human Behavior

8.2k papers and 450.4k indexed citations i.

About

The 8.2k papers published in Computers in Human Behavior in the last decades have received a total of 450.4k indexed citations. Papers published in Computers in Human Behavior usually cover Sociology and Political Science (4.2k papers), Social Psychology (1.7k papers) and Education (1.6k papers) specifically the topics of Impact of Technology on Adolescents (2.3k papers), Digital Marketing and Social Media (1.3k papers) and Technology Adoption and User Behaviour (1.2k papers). The most active scholars publishing in Computers in Human Behavior are Richard A. Davis, Donghee Shin, Robert S. Tokunaga, Scott E. Caplan, Daniel Kardefelt‐Winther, Juho Hamari, Paul A. Kirschner, Yair Amichai‐Hamburger, Tiago Oliveira and Tao Zhou.

In The Last Decade

Fields of papers published in Computers in Human Behavior

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Computers in Human Behavior. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Computers in Human Behavior.

Countries where authors publish in Computers in Human Behavior

Since Specialization
Citations

This map shows the geographic impact of research published in Computers in Human Behavior. 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 published in Computers in Human Behavior with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Computers in Human Behavior 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