World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
84
Citations
30536
World Ranking
848
National Ranking
464

Claire Cardie publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Claire Cardie sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 236 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Claire Cardie D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Claire Cardie sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 84 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 2019 - ACM Fellow For contributions to natural language processing, including coreference resolution, information and opinion extraction

Overview

Claire Cardie is affiliated with Cornell University in the United States. Their research primarily focuses on computer science, with a strong concentration in artificial intelligence. They have contributed to numerous studies across several subfields, including computer vision and pattern recognition, information systems, communication, and statistical and nonlinear physics.

Their work spans a variety of topics, with significant attention to topic modeling and natural language processing techniques. Other areas of interest include multimodal machine learning applications, advanced text analysis techniques, generative adversarial networks and image synthesis, sentiment analysis and opinion mining, as well as text readability and simplification.

Claire Cardie has a substantial publication record featuring papers in key venues. Notable recent papers include:

  • "A Measure of Polarization on Social Media Networks Based on Community Boundaries" (2021) published in the Proceedings of the International AAAI Conference on Web and Social Media
  • "Faithful or Extractive? On Mitigating the Faithfulness-Abstractiveness Trade-off in Abstractive Summarization" (2022) published in the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • "Properties, Prediction, and Prevalence of Useful User-Generated Comments for Descriptive Annotation of Social Media Objects" (2021) also in the Proceedings of the International AAAI Conference on Web and Social Media
  • "Event Extraction by Answering (Almost) Natural Questions" (2020) published on arXiv (Cornell University)
  • "Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension" (2020) published in Transactions of the Association for Computational Linguistics

The scientist frequently publishes in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Proceedings of the International AAAI Conference on Web and Social Media
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Transactions of the Association for Computational Linguistics

Collaborations occur often with the following coauthors:

  • Serge Belongie
  • Menglin Jia
  • Xinya Du
  • Dong Yu
  • Ser-Nam Lim

Claire Cardie was recognized as an ACM Fellow in 2019 for contributions to natural language processing, including coreference resolution, information and opinion extraction.

Best Publications

  • Constrained K-means Clustering with Background Knowledge

    Kiri Wagstaff;Claire Cardie;Seth Rogers;Stefan Schrödl

  • Annotating Expressions of Opinions and Emotions in Language

    Janyce Wiebe;Theresa Wilson;Claire Cardie

  • Clustering with Instance-level Constraints

    Kiri Wagstaff;Claire Cardie

  • Finding Deceptive Opinion Spam by Any Stretch of the Imagination

    Myle Ott;Yejin Choi;Claire Cardie;Jeffrey T. Hancock

  • Improving Machine Learning Approaches to Coreference Resolution

    Vincent Ng;Claire Cardie

  • OpinionFinder: A System for Subjectivity Analysis

    Theresa Wilson;Paul Hoffmann;Swapna Somasundaran;Jason Kessler

  • Learning to Ask: Neural Question Generation for Reading Comprehension

    Xinya Du;Junru Shao;Claire Cardie

  • SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability

    Eneko Agirre;Carmen Banea;Claire Cardie;Daniel Cer

  • SemEval-2014 Task 10: Multilingual Semantic Textual Similarity

    Eneko Agirre;Carmen Banea;Claire Cardie;Daniel Cer

  • Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns

    Yejin Choi;Claire Cardie;Ellen Riloff;Siddharth Patwardhan

  • Using decision trees to improve case-based learning

    Claire Cardie

  • Opinion Mining with Deep Recurrent Neural Networks

    Ozan Irsoy;Claire Cardie

  • Empirical Methods in Information Extraction

    Claire Cardie

  • Towards a General Rule for Identifying Deceptive Opinion Spam

    Jiwei Li;Myle Ott;Claire Cardie;Eduard Hovy

  • Learning with Compositional Semantics as Structural Inference for Subsentential Sentiment Analysis

    Yejin Choi;Claire Cardie

  • Event Extraction by Answering (Almost) Natural Questions

    Xinya Du;Claire Cardie

  • Negative Deceptive Opinion Spam

    Myle Ott;Claire Cardie;Jeffrey T. Hancock

  • Estimating the prevalence of deception in online review communities

    Myle Ott;Claire Cardie;Jeff Hancock

  • System and method for automatically summarizing fine-grained opinions in digital text

    Claire Cardie;Veselin Stoyanov;Yejin Choi;Eric Breck

  • Deep Recursive Neural Networks for Compositionality in Language

    Ozan Irsoy;Claire Cardie

  • Identifying Sources of Opinions with Conditional Random Fields and

    Yejin Choi;Claire Cardie;Ellen Riloff;Siddharth Patwardhan

Frequent Co-Authors

Yejin Choi
Yejin Choi Stanford University
Ellen Riloff
Ellen Riloff University of Utah
Veselin Stoyanov
Veselin Stoyanov Facebook (United States)
Janyce Wiebe
Janyce Wiebe University of Pittsburgh
Myle Ott
Myle Ott Facebook (United States)
Vincent Ng
Vincent Ng The University of Texas at Dallas
Jiwei Li
Jiwei Li Zhejiang University
Jeffrey T. Hancock
Jeffrey T. Hancock Stanford University
Diane J. Litman
Diane J. Litman University of Pittsburgh
Kiri L. Wagstaff
Kiri L. Wagstaff Oregon State University

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