World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
86
Citations
36254
World Ranking
759
National Ranking
405

Rada Mihalcea 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 Rada Mihalcea 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 371 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Rada Mihalcea 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 Rada Mihalcea sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 86 D-Index — 95th percentile

95% 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

  • 2021 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to natural language processing and computational social science.
  • 2019 - ACM Fellow For contributions to natural language processing, with innovations in data-driven and graph-based language processing

Overview

Rada Mihalcea is affiliated with the University of Michigan-Ann Arbor in the United States. Their research primarily spans the field of Computer Science, with a focus on Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science, Social Psychology, and Experimental and Cognitive Psychology.

Their work covers a range of main topics including:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Misinformation and Its Impacts
  • Sentiment Analysis and Opinion Mining
  • Multimodal Machine Learning Applications
  • Mental Health via Writing
  • Advanced Text Analysis Techniques

Rada Mihalcea has published extensively in multiple venues, with frequent contributions to:

  • arXiv (Cornell University)
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Proceedings of the International AAAI Conference on Web and Social Media
  • Cognitive Computation

Recent papers illustrate a variety of thematic focuses and publication outlets. Examples include:

  • "A review of deep learning techniques for speech processing," 2023, Information Fusion
  • "Deep Learning for Text Style Transfer: A Survey," 2021, Computational Linguistics
  • "Values in Words: Using Language to Evaluate and Understand Personal Values," 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "TikTok and prostate cancer: misinformation and quality of information using validated questionnaires," 2021, British Journal of Urology
  • "Multimodal Deception Detection Using Real-Life Trial Data," 2020, IEEE Transactions on Affective Computing

The researcher frequently collaborates with a set of co-authors, notably:

  • Soujanya Poria (26 joint publications)
  • Navonil Majumder (21 joint publications)
  • Verónica Pérez-Rosas (21 joint publications)
  • Zhijing Jin (19 joint publications)
  • Oana Ignat (17 joint publications)

Recognition for their contributions includes being named a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2021 for significant work in natural language processing and computational social science. In 2019, they were inducted as an ACM Fellow for contributions to natural language processing, with innovations in data-driven and graph-based language processing.

Best Publications

  • TextRank: Bringing Order into Text

    Rada Mihalcea;Paul Tarau

  • Corpus-based and knowledge-based measures of text semantic similarity

    Rada Mihalcea;Courtney Corley;Carlo Strapparava

  • Book Reviews: The Text Mining Handbook: Advanced Approaches to Analyzing Unstructured Data by Ronen Feldman and James Sanger

    Unknown

  • Wikify!: linking documents to encyclopedic knowledge

    Rada Mihalcea;Andras Csomai

  • SemEval-2007 Task 14: Affective Text

    Carlo Strapparava;Rada Mihalcea

  • Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

    Rada Mihalcea;Joyce Chai;Anoop Sarkar

  • Learning to identify emotions in text

    Carlo Strapparava;Rada Mihalcea

  • Graph-based ranking algorithms for sentence extraction, applied to text summarization

    Rada Mihalcea

  • Automatic Detection of Fake News

    Verónica Pérez-Rosas;Bennett Kleinberg;Alexandra Lefevre;Rada Mihalcea

  • SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation

    Eneko Agirre;Carmen Banea;Daniel M. Cer;Mona T. Diab

  • 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

  • Learning Multilingual Subjective Language via Cross-Lingual Projections

    Rada Mihalcea;Carmen Banea;Janyce Wiebe

  • Towards multimodal sentiment analysis: harvesting opinions from the web

    Louis-Philippe Morency;Rada Mihalcea;Payal Doshi

  • Unsupervised Large-Vocabulary Word Sense Disambiguation with Graph-based Algorithms for Sequence Data Labeling

    Rada Mihalcea

  • Measuring the Semantic Similarity of Texts

    Courtney Corley;Rada Mihalcea

  • Using Wikipedia for Automatic Word Sense Disambiguation

    Rada Mihalcea

  • ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection.

    Devamanyu Hazarika;Soujanya Poria;Rada Mihalcea;Erik Cambria

  • The Lie Detector: Explorations in the Automatic Recognition of Deceptive Language

    Rada Mihalcea;Carlo Strapparava

  • Unsupervised Graph-basedWord Sense Disambiguation Using Measures of Word Semantic Similarity

    R. Sinha;R. Mihalcea

  • Text-to-Text Semantic Similarity for Automatic Short Answer Grading

    Michael Mohler;Rada Mihalcea

  • Word Sense and Subjectivity

    Janyce Wiebe;Rada Mihalcea

Frequent Co-Authors

Janyce Wiebe
Janyce Wiebe University of Pittsburgh
Soujanya Poria
Soujanya Poria Nanyang Technological University
Dragomir R. Radev
Dragomir R. Radev Yale University
Carlo Strapparava
Carlo Strapparava Fondazione Bruno Kessler
Dan Moldovan
Dan Moldovan The University of Texas at Dallas
Jia Deng
Jia Deng Princeton University
Razvan Bunescu
Razvan Bunescu University of North Carolina at Charlotte
Erik Cambria
Erik Cambria Nanyang Technological University
Roger Zimmermann
Roger Zimmermann National University of Singapore
James W. Pennebaker
James W. Pennebaker The University of Texas at Austin

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