Mark Dredze
- Health Informatics top 0.05%
- Artificial Intelligence top 0.05%
- Topic Modeling 89
- Natural Language Processing Techniques 61
- Applied Psychology top 0.5%
- Health top 0.2%
- Vaccine Coverage and Hesitancy 18
- Social Media in Health Education 18
- Communication top 0.5%
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- Misinformation and Its Impacts 42
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- Data-Driven Disease Surveillance 40
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- Smoking Behavior and Cessation 17
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- Mental Health via Writing 17
- Co-authors
- Fernando PereiraMichael J. PaulGlen CoppersmithJohn BlitzerDavid BroniatowskiJohn W. AyersKoby CrammerCraig Harman
- Journals
- JAMA Internal Medicine (10 papers)PLoS ONE (8 papers)Journal of Medical Internet Research (6 papers)
- Partner nations
- United StatesUnited KingdomIreland
In The Last Decade
Mark Dredze
236 papers receiving 12.9k citations
Hit Papers
Peers
Comparison fields: 5 of 192
- Health Informatics 861
- Artificial Intelligence 6.9k
- Applied Psychology 1.0k
- Health 1.5k
- Communication 817
Countries citing papers authored by Mark Dredze
This map shows the geographic impact of Mark Dredze'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 Mark Dredze with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Dredze more than expected).
Fields of papers citing papers by Mark Dredze
This network shows the impact of papers produced by Mark Dredze. 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 Mark Dredze. The network helps show where Mark Dredze may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mark Dredze, 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 | 0 | |
| 3 | 2025 | 6 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 8 | |
| 7 | Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forumbreakdown → | 2023 | 1184 |
| 8 | 2023 | 11 | |
| 9 | 2022 | 1 | |
| 10 | 2020 | 11 | |
| 11 | 2020 | 26 | |
| 12 | 2020 | 30 | |
| 13 | 2019 | 29 | |
| 14 | 2018 | 5 | |
| 15 | 2018 | 26 | |
| 16 | 2016 | 49 | |
| 17 | 2015 | 40 | |
| 18 | Quantifying Mental Health Signals in Twitterbreakdown → | 2014 | 427 |
| 19 | PARMA: A Predicate Argument Aligner | 2013 | 9 |
| 20 | Information retrieval and knowledge discovery in biomedical text : papers from the AAAI Fall Symposium | 2012 | 1 |
About Mark Dredze
Mark Dredze is a scholar working on Health, Artificial Intelligence and General Social Sciences, having authored 251 papers that have together received 13.8k indexed citations. Recurring topics across this work include Topic Modeling (89 papers), Natural Language Processing Techniques (61 papers), Misinformation and Its Impacts (42 papers), Data-Driven Disease Surveillance (40 papers), Vaccine Coverage and Hesitancy (18 papers), Social Media in Health Education (18 papers), Smoking Behavior and Cessation (17 papers) and Mental Health via Writing (17 papers). The work is most often cited by research in Health Informatics (861 citations), Artificial Intelligence (6.9k citations) and Applied Psychology (1.0k citations). Mark Dredze has collaborated with scholars based in United States, United Kingdom and Ireland. Frequent co-authors include Fernando Pereira, Michael J. Paul, Glen Coppersmith, John Blitzer, David Broniatowski, John W. Ayers, Koby Crammer, Craig Harman, Eric C. Leas and Nanyun Peng. Their work appears in journals such as JAMA Internal Medicine, PLoS ONE, Journal of Medical Internet Research, Vaccine and American Journal of Preventive Medicine.
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.