Chloé Braud
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Speech and dialogue systems
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Text Readability and Simplification
- Text and Document Classification Technologies
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- Multimodal Machine Learning Applications
Papers in
-
- Topic Modeling 8
- Natural Language Processing Techniques 7
- Speech and dialogue systems 4
- Sentiment Analysis and Opinion Mining 2
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- Computational and Text Analysis Methods 1
- Co-authors
- Pascal DenisAnders SøgaardBarbara PlankAngela FanClaire GardentAntoine BordesChuyuan LiPhilippe Müller
- Journals
- Transactions of the Association for Computational Linguistics (1 paper)SPIRE - Sciences Po Institutional REpository (1 paper)Research at the University of Copenhagen (University of Copenhagen) (2 papers)HAL (Le Centre pour la Communication Scientifique Directe) (2 papers)
In The Last Decade
Chloé Braud
11 papers receiving 146 citations
Peers
Comparison fields: 5 of 28
- Artificial Intelligence 142
- Computer Vision and Pattern Recognition 31
- Applied Psychology 5
- Health Informatics 1
- Information Systems 14
Countries citing papers authored by Chloé Braud
This map shows the geographic impact of Chloé Braud'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 Chloé Braud with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chloé Braud more than expected).
Fields of papers citing papers by Chloé Braud
This network shows the impact of papers produced by Chloé Braud. 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 Chloé Braud. The network helps show where Chloé Braud may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Chloé Braud, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 1 | |
| 2 | 2023 | 3 | |
| 3 | 2023 | 1 | |
| 4 | 2022 | 11 | |
| 5 | 2021 | 26 | |
| 6 | 2021 | 7 | |
| 7 | 2017 | 2 | |
| 8 | 2016 | 25 | |
| 9 | The 26th International Conference on Computational Linguistics (COLING) | 2016 | 11 |
| 10 | 2016 | 22 | |
| 11 | 2015 | 47 |
About Chloé Braud
Chloé Braud is a scholar working on Artificial Intelligence, General Social Sciences, Applied Psychology, Computer Vision and Pattern Recognition and Social Psychology, having authored 11 papers that have together received 156 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (7 papers), Speech and dialogue systems (4 papers), Misinformation and Its Impacts (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Digital Mental Health Interventions (1 paper), Computational and Text Analysis Methods (1 paper) and Media Influence and Politics (1 paper). The work is most often cited by research in Artificial Intelligence (142 citations), Computer Vision and Pattern Recognition (31 citations), Applied Psychology (5 citations), Health Informatics (1 citation) and Information Systems (14 citations). Chloé Braud has collaborated with scholars based in France, Denmark and Spain. Frequent co-authors include Pascal Denis, Anders Søgaard, Barbara Plank, Angela Fan, Claire Gardent, Antoine Bordes, Chuyuan Li, Philippe Müller, Amir Zeldes and Xiao Wen. Their work appears in journals such as Transactions of the Association for Computational Linguistics, SPIRE - Sciences Po Institutional REpository, Research at the University of Copenhagen (University of Copenhagen) and HAL (Le Centre pour la Communication Scientifique Directe).
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.