Thomas François

1.4k total citations
62 papers, 781 citations indexed

About

Thomas François is a scholar working on Artificial Intelligence, Language and Linguistics and Developmental and Educational Psychology. According to data from OpenAlex, Thomas François has authored 62 papers receiving a total of 781 indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Artificial Intelligence, 10 papers in Language and Linguistics and 9 papers in Developmental and Educational Psychology. Recurrent topics in Thomas François's work include Text Readability and Simplification (37 papers), Natural Language Processing Techniques (36 papers) and Topic Modeling (11 papers). Thomas François is often cited by papers focused on Text Readability and Simplification (37 papers), Natural Language Processing Techniques (36 papers) and Topic Modeling (11 papers). Thomas François collaborates with scholars based in Belgium, France and United States. Thomas François's co-authors include Cédrick Fairon, Piet Desmet, Philippe Yamato, E. Burov, Evgueni Burov, Eleni Miltsakaki, Sylvie Wolf, Bertrand Meyer, Philippe Agard and Liviu Maţenco and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Earth and Planetary Science Letters.

In The Last Decade

Thomas François

56 papers receiving 712 citations

Peers

Thomas François
Comparison fields: 5 of 80
  • Artificial Intelligence 450
  • Geophysics 226
  • Developmental and Educational Psychology 113
  • Language and Linguistics 85
  • General Health Professions 42
Replace Donia R. Scott with:
Donia R. Scott United Kingdom
Michael Carr United States
Federica Raia United States
Rosa María Rodríguez Jiménez Spain
William J. Bonk United States
Ian Pringle New Zealand
Wenlan Zhang China
Heather L. Petcovic United States
Martin Pütz Germany
Donia R. Scott United Kingdom View profile →
Citations per field, relative to Thomas François
Thomas François · 1×
Citations per year, relative to Thomas François
Thomas François · 1×

Countries citing papers authored by Thomas François

Since Specialization
Citations

This map shows the geographic impact of Thomas François's research. 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 Thomas François with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas François more than expected).

Fields of papers citing papers by Thomas François

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas François. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Thomas François. The network helps show where Thomas François may publish in the future.

Co-authorship network of co-authors of Thomas François

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas François. A scholar is included among the top collaborators of Thomas François based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Thomas François. Thomas François is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 4
3 3
4 34
5 31
6 1
7 2
8 3
9 4
10 4
11
EFLLex: A Graded Lexical Resource for Learners of English as a Foreign Language
16
12 8
13
Introducing NT2Lex: A Machine-readable CEFR-graded Lexical Resource for Dutch as a Foreign Language
1
14
SVALex: a CEFR-graded Lexical Resource for Swedish Foreign and Second Language Learners
19
15
Automatic annotation of medical reports using SNOMED-CT: a flexible approach based on medical knowledge databases
1
16
Automatic extraction of contextual valence shifters.
5
17 69
18
On the Contribution of MWE-based Features to a Readability Formula for French as a Foreign Language
13
19
An N-gram Frequency Database Reference to Handle MWE Extraction in NLP Applications
4
20 3

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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