Nathan Gilbert
- Artificial Intelligence top 2%
- Topic Modeling 5
- Natural Language Processing Techniques 4
- Advanced Text Analysis Techniques 2
- Sentiment Analysis and Opinion Mining 2
- Information Systems top 10%
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- Immunotherapy and Immune Responses 4
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- CAR-T cell therapy research 3
- Cancer Immunotherapy and Biomarkers 2
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- Cancer Research and Treatments 2
Nathan Gilbert
11 papers receiving 497 citations
Hit Papers
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 488
- Information Systems 65
- Experimental and Cognitive Psychology 36
- Human-Computer Interaction 8
- Social Psychology 28
Countries citing papers authored by Nathan Gilbert
This map shows the geographic impact of Nathan Gilbert'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 Nathan Gilbert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan Gilbert more than expected).
Fields of papers citing papers by Nathan Gilbert
This network shows the impact of papers produced by Nathan Gilbert. 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 Nathan Gilbert. The network helps show where Nathan Gilbert may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nathan Gilbert, 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 | 2025 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 1 | |
| 5 | Sarcasm as Contrast between a Positive Sentiment and Negative Situationbreakdown → | 2013 | 353 |
| 6 | Domain-Specific Coreference Resolution with Lexicalized Features | 2013 | 5 |
| 7 | The Taming of Reconcile as a Biomedical Coreference Resolver | 2011 | 19 |
| 8 | Coreference Resolution with Reconcile | 2010 | 62 |
| 9 | Toward Plot Units: Automatic Affect State Analysis | 2010 | 8 |
| 10 | 2009 | 93 | |
| 11 | 1952 | 25 |
About Nathan Gilbert
Nathan Gilbert is a scholar working on Biotechnology, Immunology, Artificial Intelligence, Oncology and Experimental and Cognitive Psychology, having authored 11 papers that have together received 569 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Immunotherapy and Immune Responses (4 papers), Natural Language Processing Techniques (4 papers), CAR-T cell therapy research (3 papers), Cancer Immunotherapy and Biomarkers (2 papers), Advanced Text Analysis Techniques (2 papers), Cancer Research and Treatments (2 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Artificial Intelligence (488 citations), Information Systems (65 citations), Experimental and Cognitive Psychology (36 citations), Human-Computer Interaction (8 citations) and Social Psychology (28 citations). Nathan Gilbert has collaborated with scholars based in United States. Frequent co-authors include Ellen Riloff, Ashequl Qadir, Lalindra De Silva, Ruihong Huang, Veselin Stoyanov, Claire Cardie, David Buttler, David Hysom, Young-Jun Kim and Amit Goyal. Their work appears in journals such as International Journal of Molecular Sciences, Annals of Oncology, Cancer Research, SHILAP Revista de lepidopterología and North American Chapter of the Association for Computational Linguistics.
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.