Quantitative Analysis of Culture Using Millions of Digitized Books
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doi.org/10.1126/science.1199644 →Countries where authors are citing Quantitative Analysis of Culture Using Millions of Digitized Books
This map shows the geographic impact of Quantitative Analysis of Culture Using Millions of Digitized Books. 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 Quantitative Analysis of Culture Using Millions of Digitized Books with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quantitative Analysis of Culture Using Millions of Digitized Books more than expected).
Fields of papers citing Quantitative Analysis of Culture Using Millions of Digitized Books
This network shows the impact of Quantitative Analysis of Culture Using Millions of Digitized Books. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Quantitative Analysis of Culture Using Millions of Digitized Books.
About Quantitative Analysis of Culture Using Millions of Digitized Books
This paper, published in 2010, received 1.9k indexed citations . Written by Jean-Baptiste Michel, Yuan Kui Shen, Aviva Presser Aiden, Adrian Veres, Matthew K. Gray, Peter Norvig, Jon Orwant, Steven A. Pinker, Martin Nowak and Erez Lieberman Aiden covering the research area of Artificial Intelligence, Cultural Studies and Language and Linguistics. It is primarily cited by scholars working on Artificial Intelligence (611 citations), Sociology and Political Science (414 citations), Cultural Studies (384 citations), Social Psychology (189 citations) and Literature and Literary Theory (177 citations). Published in Science.
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/10.1126/science.1199644.