World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
9206
World Ranking
7893
National Ranking
317

Diana Inkpen 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 Diana Inkpen 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: 212 publications — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Diana Inkpen 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 Diana Inkpen 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Diana Inkpen is affiliated with the University of Ottawa in Canada. Their research primarily spans the field of Computer Science with a focused presence in subfields such as Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Social Psychology, and Signal Processing.

The main topics covered in their work include:

  • Topic Modeling
  • Text and Document Classification Technologies
  • Domain Adaptation and Few-Shot Learning
  • Mental Health via Writing
  • Sentiment Analysis and Opinion Mining
  • Natural Language Processing Techniques
  • Web Data Mining and Analysis

Inkpen has published extensively in various venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Computational Intelligence
  • Journal of Information and Organizational Sciences
  • Proceedings of the International Florida Artificial Intelligence Research Society Conference
  • ACM Computing Surveys

Notable recent papers authored or co-authored by Diana Inkpen are:

  • "Using Social Media for Mental Health Surveillance," 2020, ACM Computing Surveys
  • "A multi-platform dataset for detecting cyberbullying in social media," 2020, Language Resources and Evaluation
  • "Predicting Depression in Canada by Automatic Filling of Beck's Depression Inventory Questionnaire," 2022, IEEE Access
  • "Multi-task learning to detect suicide ideation and mental disorders among social media users," 2023, Frontiers in Research Metrics and Analytics
  • "Dual Mixup Regularized Learning for Adversarial Domain Adaptation," 2020, arXiv (Cornell University)

Frequent co-authors in their research collaborations include:

  • Ahmed El-Roby
  • Anna Atefeh Farzindar
  • Yuan Wu
  • Falah Al-akashi
  • Gerhard Lakemeyer

In addition to journal and conference publications, Diana Inkpen has contributed to book literature. They have published a book titled Natural Language Processing for Social Media in 2020 with Morgan & Claypool Publishers.

Best Publications

  • Enhanced LSTM for Natural Language Inference

    Qian Chen;Xiaodan Zhu;Zhen-Hua Ling;Si Wei

  • SENTIMENT CLASSIFICATION of MOVIE REVIEWS USING CONTEXTUAL VALENCE SHIFTERS

    Alistair Kennedy;Diana Inkpen

  • Semantic text similarity using corpus-based word similarity and string similarity

    Aminul Islam;Diana Inkpen

  • Offensive language detection using multi-level classification

    Amir H. Razavi;Diana Inkpen;Sasha Uritsky;Stan Matwin

  • Deep Learning for Depression Detection of Twitter Users

    Ahmed Husseini Orabi;Prasadith Buddhitha;Mahmoud Husseini Orabi;Diana Inkpen

  • Neural Natural Language Inference Models Enhanced with External Knowledge

    Qian Chen;Xiaodan Zhu;Zhen-Hua Ling;Diana Inkpen

  • Detecting Emotion Stimuli in Emotion-Bearing Sentences

    Diman Ghazi;Diana Inkpen;Stan Szpakowicz

  • Sentiment Classification of Movie and Product Reviews Using Contextual Valence Shifters

    Alistair Kennedy;Diana Inkpen

  • Using a heterogeneous dataset for emotion analysis in text

    Soumaya Chaffar;Diana Inkpen

  • Building and Using a Lexical Knowledge Base of Near-Synonym Differences

    Diana Inkpen;Graeme Hirst

  • Second Order Co-occurrence PMI for Determining the Semantic Similarity of Words

    Aminul Islam;Diana Inkpen

  • Natural Language Processing for Social Media

    Atefeh Farzindar;Diana Inkpen

  • Dual Mixup Regularized Learning for Adversarial Domain Adaptation

    Yuan Wu;Diana Inkpen;Ahmed El-Roby

  • Real-Word Spelling Correction using Google Web 1T 3-grams

    Aminul Islam;Diana Inkpen

  • A Dataset for Multi-Target Stance Detection.

    Parinaz Sobhani;Diana Inkpen;Xiaodan Zhu

  • Using Social Media for Mental Health Surveillance: A Review

    Ruba Skaik;Diana Inkpen

  • A new algorithm for reducing the workload of experts in performing systematic reviews

    Stan Matwin;Stan Matwin;Alexandre Kouznetsov;Diana Inkpen;Oana Frunza

  • Hierarchical versus Flat Classification of Emotions in Text

    Diman Ghazi;Diana Inkpen;Stan Szpakowicz

  • Identification of translationese: a machine learning approach

    Iustina Ilisei;Diana Inkpen;Gloria Corpas Pastor;Ruslan Mitkov

  • Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text

    Diana Inkpen;Carlo Strapparava

  • A Machine Learning Approach for Identifying Disease-Treatment Relations in Short Texts

    O Frunza;D Inkpen;T Tran

  • Recurrent Neural Network-Based Sentence Encoder with Gated Attention for Natural Language Inference

    Qian Chen;Xiaodan Zhu;Zhen-Hua Ling;Si Wei

Frequent Co-Authors

Stan Szpakowicz
Stan Szpakowicz University of Ottawa
Stan Matwin
Stan Matwin Dalhousie University
Xiaodan Zhu
Xiaodan Zhu Queen's University
Graeme Hirst
Graeme Hirst University of Toronto
Zhen-Hua Ling
Zhen-Hua Ling University of Science and Technology of China
Hui Jiang
Hui Jiang York University
Carlo Strapparava
Carlo Strapparava Fondazione Bruno Kessler
Michael Gamon
Michael Gamon Microsoft (United States)
Emil M. Petriu
Emil M. Petriu University of Ottawa
Amiya Nayak
Amiya Nayak University of Ottawa

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