Modèles Dynamiques Corpus

919 papers and 4.4k indexed citations

About

In recent decades, authors affiliated with Modèles Dynamiques Corpus have published 919 papers, which have received a total of 4.4k indexed citations. Scholars at this organization have produced 487 papers in Philosophy, 385 papers in Language and Linguistics and 346 papers in Linguistics and Language on the topics of Linguistics and Discourse Analysis (485 papers), French Language Learning Methods (278 papers) and Historical Linguistics and Language Studies (206 papers). Their work is cited by papers focused on Language and Linguistics (1.6k citations), Philosophy (1.5k citations) and Linguistics and Language (1.3k citations). Authors at Modèles Dynamiques Corpus collaborate with scholars in France, Belgium and United States and have published in prestigious journals including Nucleic Acids Research, SHILAP Revista de lepidopterología and PLoS ONE. Some of Modèles Dynamiques Corpus's most productive authors include Bernard Laks, Jacques Durand, Françoise Gadet, Michael J. Baker, Christophe Parisse, Danielle Leeman, Didier Bottineau, Edy Veneziano, Chantal Lyche and Michel Arrivé.

In The Last Decade

Modèles Dynamiques Corpus

737 papers receiving 4.3k citations

Countries citing scholars working at Modèles Dynamiques Corpus

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Modèles Dynamiques Corpus. 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 produced at Modèles Dynamiques Corpus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Modèles Dynamiques Corpus more than expected).

Fields of papers published by authors at Modèles Dynamiques Corpus

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Modèles Dynamiques Corpus at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Modèles Dynamiques Corpus at the time of their publication.

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.

Explore institutions with similar magnitude of impact

Rankless by CCL
2026