Rachel Bawden
- Artificial Intelligence
- Language and Linguistics top 10%
- Experimental and Cognitive Psychology
- Computer Vision and Pattern Recognition
- Developmental and Educational Psychology
- Co-authors
- Barry HaddowJindřich HelclAlexandra BirchAntonio Valerio Miceli BaroneBenoît SagotSylvain KahaneKim GerdesAntonio Jimeno Yepes
- Topics
- Natural Language Processing Techniques (9 papers)Topic Modeling (5 papers)Text Readability and Simplification (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaComputational LinguisticsLanguage Resources and Evaluation
- Partner nations
- FranceUnited KingdomUnited States
In The Last Decade
Rachel Bawden
10 papers receiving 101 citations
Peers
Comparison fields: 5 of 39
- Artificial Intelligence 70
- Language and Linguistics 22
- Experimental and Cognitive Psychology 19
- Computer Vision and Pattern Recognition 16
- Developmental and Educational Psychology 9
Countries citing papers authored by Rachel Bawden
This map shows the geographic impact of Rachel Bawden'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 Rachel Bawden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rachel Bawden more than expected).
Fields of papers citing papers by Rachel Bawden
This network shows the impact of papers produced by Rachel Bawden. 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 Rachel Bawden. The network helps show where Rachel Bawden may publish in the future.
Co-authorship network of co-authors of Rachel Bawden
This figure shows the co-authorship network connecting the top 25 collaborators of Rachel Bawden. A scholar is included among the top collaborators of Rachel Bawden 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 Rachel Bawden. Rachel Bawden is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 12 | |
| 6 | 1 | |
| 7 | 48 | |
| 8 | 1 | |
| 9 | 31 | |
| 10 | 1 | |
| 11 | Global Under-Resourced Media Translation (GoURMET) | 3 |
| 12 | 0 | |
| 13 | Correcting and Validating Syntactic Dependency in the Spoken French Treebank Rhapsodie | 2 |
About Rachel Bawden
Rachel Bawden is a scholar working on Language and Linguistics, Artificial Intelligence and Philosophy, having authored 13 papers that have together received 103 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Topic Modeling (5 papers) and Text Readability and Simplification (5 papers). The work is most often cited by research in Health Informatics (3 citations), Artificial Intelligence (70 citations) and Language and Linguistics (22 citations). Rachel Bawden has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Barry Haddow, Jindřich Helcl, Alexandra Birch, Antonio Valerio Miceli Barone, Benoît Sagot, Sylvain Kahane, Kim Gerdes, Antonio Jimeno Yepes, Philippe Thomas and Miquel Esplà-Gomis. Their work appears in journals such as SHILAP Revista de lepidopterología, Computational Linguistics and Language Resources and Evaluation.
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.