Claire Cardie
- Artificial Intelligence top 0.02%
- Topic Modeling 123
- Natural Language Processing Techniques 92
- Sentiment Analysis and Opinion Mining 41
- Advanced Text Analysis Techniques 39
- Speech and dialogue systems 16
- Text Readability and Simplification 10
- Information Systems top 0.1%
- Spam and Phishing Detection 9
- Signal Processing top 1%
-
- Misinformation and Its Impacts 10
- Co-authors
- Janyce WiebeYejin ChoiKiri L. WagstaffTheresa WilsonStefan SchrödlSeth RogersVincent NgMyle Ott
- Partner nations
- United StatesIsraelChina
In The Last Decade
Claire Cardie
171 papers receiving 11.1k citations
Hit Papers
Peers
Comparison fields: 5 of 187
- Artificial Intelligence 10.4k
- Information Systems 2.5k
- Computer Vision and Pattern Recognition 1.4k
- Signal Processing 681
- Statistical and Nonlinear Physics 484
Countries citing papers authored by Claire Cardie
This map shows the geographic impact of Claire Cardie'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 Claire Cardie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claire Cardie more than expected).
Fields of papers citing papers by Claire Cardie
This network shows the impact of papers produced by Claire Cardie. 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 Claire Cardie. The network helps show where Claire Cardie may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Claire Cardie, 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 | 0 | |
| 2 | 2020 | 32 | |
| 3 | 2020 | 85 | |
| 4 | 2020 | 225 | |
| 5 | Probing Prior Knowledge Needed in Challenging Chinese Machine Reading Comprehension. | 2019 | 6 |
| 6 | 2018 | 67 | |
| 7 | 2017 | 159 | |
| 8 | 2016 | 68 | |
| 9 | Modeling Compositionality with Multiplicative Recurrent Neural Networks | 2015 | 6 |
| 10 | Joint Inference for Fine-grained Opinion Extraction | 2013 | 132 |
| 11 | Domain-Independent Abstract Generation for Focused Meeting Summarization | 2013 | 56 |
| 12 | Hierarchical Sequential Learning for Extracting Opinions and Their Attributes | 2010 | 74 |
| 13 | Coreference Resolution with Reconcile | 2010 | 62 |
| 14 | Rulemaking 2.0 | 2010 | 2 |
| 15 | Multi-Level Structured Models for Document-Level Sentiment Classification | 2010 | 129 |
| 16 | An eRulemaking Corpus: Identifying Substantive Issues in Public Comments | 2008 | 6 |
| 17 | Combining Low-Level and Summary Representations of Opinions for Multi-Perspective Question Answering | 2003 | 55 |
| 18 | Limitations of Co-Training for Natural Language Learning from Large Datasets | 2001 | 121 |
| 19 | Clustering with Instance-Level Constraints | 2000 | 38 |
| 20 | SMART High Precision: TREC 7. | 1998 | 11 |
About Claire Cardie
Claire Cardie is a scholar working on Artificial Intelligence, Information Systems and Communication, having authored 176 papers that have together received 12.4k indexed citations. Recurring topics across this work include Topic Modeling (123 papers), Natural Language Processing Techniques (92 papers), Sentiment Analysis and Opinion Mining (41 papers), Advanced Text Analysis Techniques (39 papers), Speech and dialogue systems (16 papers), Misinformation and Its Impacts (10 papers), Text Readability and Simplification (10 papers) and Spam and Phishing Detection (9 papers). The work is most often cited by research in Artificial Intelligence (10.4k citations), Information Systems (2.5k citations) and Computer Vision and Pattern Recognition (1.4k citations). Claire Cardie has collaborated with scholars based in United States, Israel and China. Frequent co-authors include Janyce Wiebe, Yejin Choi, Kiri L. Wagstaff, Theresa Wilson, Stefan Schrödl, Seth Rogers, Vincent Ng, Myle Ott, Xinya Du and Jeffrey T. Hancock.
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.