Verna Dankers
Impact in
- Artificial Intelligence top 5%
- Natural Language Processing Techniques
- Topic Modeling
- Sentiment Analysis and Opinion Mining
- Domain Adaptation and Few-Shot Learning
- Text Readability and Simplification
- Advanced Text Analysis Techniques
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- Language, Metaphor, and Cognition
Papers in
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- Natural Language Processing Techniques 10
- Topic Modeling 8
- Sentiment Analysis and Opinion Mining 3
- Text Readability and Simplification 2
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- Language, Metaphor, and Cognition 4
- Co-authors
- Dieuwke Hupkes (6 shared papers)Elia Bruni (3 shared papers)Mathijs Mul (2 shared papers)Ekaterina Shutova (5 shared papers)Marek Rei (1 shared paper)Ivan Titov (2 shared papers)Christopher J. Lucas (1 shared paper)Agneta H. Fischer (1 shared paper)
- Journals
- Journal of Artificial Intelligence Research (1 paper)Nature Machine Intelligence (1 paper)Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (3 papers)UvA-DARE (University of Amsterdam) (3 papers)
- Partner nations
- NetherlandsUnited KingdomSouth Korea
In The Last Decade
Verna Dankers
12 papers receiving 251 citations
Peers
Comparison fields: 5 of 42
- Artificial Intelligence 228
- Experimental and Cognitive Psychology 53
- Computer Vision and Pattern Recognition 52
- General Social Sciences 5
- Health Informatics 2
Countries citing papers authored by Verna Dankers
This map shows the geographic impact of Verna Dankers'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 Verna Dankers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Verna Dankers more than expected).
Fields of papers citing papers by Verna Dankers
This network shows the impact of papers produced by Verna Dankers. 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 Verna Dankers. The network helps show where Verna Dankers may publish in the future.
Co-authors
The 25 scholars most cited alongside Verna Dankers, 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 | 2020 | 82 | |
| 2 | 2019 | 47 | |
| 3 | 2023 | 29 | |
| 4 | 2022 | 28 | |
| 5 | 2020 | 26 | |
| 6 | 2022 | 21 | |
| 7 | 2020 | 12 | |
| 8 | 2020 | 9 | |
| 9 | 2021 | 8 | |
| 10 | 2022 | 4 | |
| 11 | 2023 | 3 | |
| 12 | 2022 | 1 | |
| 13 | 2022 | 0 | |
| 14 | 2025 | 0 |
About Verna Dankers
Verna Dankers is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition, Information Systems and Literature and Literary Theory, having authored 14 papers that have together received 270 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (10 papers), Topic Modeling (8 papers), Language, Metaphor, and Cognition (4 papers), Sentiment Analysis and Opinion Mining (3 papers), Multimodal Machine Learning Applications (2 papers), Text Readability and Simplification (2 papers), Syntax, Semantics, Linguistic Variation (1 paper) and Rough Sets and Fuzzy Logic (1 paper). The work is most often cited by research in Artificial Intelligence (228 citations), Experimental and Cognitive Psychology (53 citations), Computer Vision and Pattern Recognition (52 citations), General Social Sciences (5 citations) and Health Informatics (2 citations). Verna Dankers has collaborated with scholars based in Netherlands, United Kingdom and South Korea. Frequent co-authors include Dieuwke Hupkes, Elia Bruni, Mathijs Mul, Ekaterina Shutova, Marek Rei, Ivan Titov, Christopher J. Lucas, Agneta H. Fischer, Adina Williams and Preslav Nakov. Their work appears in journals such as Journal of Artificial Intelligence Research, Nature Machine Intelligence, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) and UvA-DARE (University of Amsterdam).
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.