The general inquirer: A computer approach to content analysis.
Impact in
- Journal
- MIT Press eBooks
In The Last Decade
doi.org/w11993515 →Countries where authors are citing The general inquirer: A computer approach to content analysis.
This map shows the geographic impact of The general inquirer: A computer approach to content analysis.. 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 The general inquirer: A computer approach to content analysis. with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites The general inquirer: A computer approach to content analysis. more than expected).
Fields of papers citing The general inquirer: A computer approach to content analysis.
This network shows the impact of The general inquirer: A computer approach to content analysis.. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the The general inquirer: A computer approach to content analysis..
About The general inquirer: A computer approach to content analysis.
This paper, published in 1966, received 807 indexed citations . Written by Marshall S. Smith, Philip J. Stone and Dexter Dunphy. It is primarily cited by scholars working on Artificial Intelligence (474 citations), Sociology and Political Science (135 citations), Social Psychology (85 citations), Information Systems (71 citations) and Clinical Psychology (45 citations). Published in MIT Press eBooks.
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/w11993515.