Journal of Quantitative Linguistics

514 papers and 4.1k indexed citations i.

About

The 514 papers published in Journal of Quantitative Linguistics in the last decades have received a total of 4.1k indexed citations. Papers published in Journal of Quantitative Linguistics usually cover Artificial Intelligence (342 papers), Language and Linguistics (115 papers) and Cultural Studies (67 papers) specifically the topics of Natural Language Processing Techniques (231 papers), Authorship Attribution and Profiling (157 papers) and Topic Modeling (65 papers). The most active scholars publishing in Journal of Quantitative Linguistics are Sean Wallis, Ramon Ferrer‐i‐Cancho, Michael A. Covington, Ricard V. Solé, Jacques Savoy, Haitao Liu, William A. Gale, Dominique Labbé, Patrick Juola and Geoffrey Sampson.

In The Last Decade

Fields of papers published in Journal of Quantitative Linguistics

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Journal of Quantitative Linguistics. 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 Journal of Quantitative Linguistics.

Countries where authors publish in Journal of Quantitative Linguistics

Since Specialization
Citations

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