Modèles Dynamiques Corpus
Impact in
- Linguistics and Language top 2%
- French Language Learning Methods
- Linguistic Variation and Morphology
- Language and Linguistics top 5%
- Syntax, Semantics, Linguistic Variation
- Historical Linguistics and Language Studies
Papers in
-
- French Language Learning Methods 280
- Linguistic and Sociocultural Studies 81
- Philosophy 495
- Linguistics and Discourse Analysis 493
- Top scholars
- Bernard LaksJacques DurandFrançoise GadetMichael J. BakerChristophe ParisseDidier BottineauDanielle LeemanEdy Veneziano
- Journals
- Langue française (46 papers)Journal of French Language Studies (8 papers)First Language (5 papers)Langages (39 papers)International Journal of the Sociology of Language (3 papers)
- Partner nations
- FranceBelgiumUnited States
In The Last Decade
Modèles Dynamiques Corpus
750 papers receiving 4.5k citations
Peers
Comparison fields: 5 of 179
- Linguistics and Language 1.4k
- Language and Linguistics 1.7k
- Philosophy 1.5k
- Experimental and Cognitive Psychology 1.0k
- Developmental and Educational Psychology 935
Countries citing scholars working at Modèles Dynamiques Corpus
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
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.
About Modèles Dynamiques Corpus
In recent decades, authors affiliated with Modèles Dynamiques Corpus have published 939 papers, which have received a total of 4.8k indexed citations . Scholars at this organization have produced 353 papers in Linguistics and Language, 495 papers in Philosophy, 394 papers in Language and Linguistics, 129 papers in Experimental and Cognitive Psychology and 88 papers in Developmental and Educational Psychology on the topics of Linguistics and Discourse Analysis (493 papers), French Language Learning Methods (280 papers), Historical Linguistics and Language Studies (210 papers), Natural Language Processing Techniques (123 papers), Phonetics and Phonology Research (81 papers), Linguistic and Sociocultural Studies (81 papers), Syntax, Semantics, Linguistic Variation (80 papers) and linguistics and terminology studies (55 papers). Their work is cited by papers focused on Linguistics and Language (1.4k citations), Language and Linguistics (1.7k citations), Philosophy (1.5k citations), Experimental and Cognitive Psychology (1.0k citations) and Developmental and Educational Psychology (935 citations). Authors at Modèles Dynamiques Corpus collaborate with scholars in France, Belgium and United States and have published in prestigious journals including Langue française, Journal of French Language Studies, First Language, Langages and International Journal of the Sociology of Language. Some of Modèles Dynamiques Corpus's most productive authors include Bernard Laks, Jacques Durand, Françoise Gadet, Michael J. Baker, Christophe Parisse, Didier Bottineau, Danielle Leeman, Edy Veneziano, Chantal Lyche and Kristine Lund.
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.