World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
9871
World Ranking
11000
National Ranking
437

Svetlana Kiritchenko 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 Svetlana Kiritchenko 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: 76 publications — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Svetlana Kiritchenko 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 Svetlana Kiritchenko 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Svetlana Kiritchenko is affiliated with the National Research Council Canada. Their research contributions primarily focus on the intersection of computer science and social sciences, with a strong emphasis on artificial intelligence and its applications in social contexts.

The main fields of study in their work include:

  • Computer Science

Within this broad discipline, Kiritchenko's subfields of study cover:

  • Artificial Intelligence
  • Sociology and Political Science
  • Social Psychology
  • Communication
  • General Social Sciences

The research topics they address span both technical and social dimensions, including:

  • Hate Speech and Cyberbullying Detection
  • Explainable Artificial Intelligence (XAI)
  • Adversarial Robustness in Machine Learning
  • Social Media and Politics
  • Media Influence and Politics
  • Mental Health via Writing
  • Sentiment Analysis and Opinion Mining

Svetlana Kiritchenko has contributed to multiple publication venues. Frequent platforms for their work include:

  • arXiv (Cornell University)
  • AEA Randomized Controlled Trials
  • Journal of Social and Personal Relationships
  • 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

Recent papers by Kiritchenko illustrate a blend of social science and machine learning topics, such as:

  • Examining the language of solitude versus loneliness in tweets, 2021, Journal of Social and Personal Relationships
  • Using Nuances of Emotion to Identify Personality, 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection, 2022, Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Improving Generalizability in Implicitly Abusive Language Detection with Concept Activation Vectors, 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Detecting AI-Generated Text: Factors Influencing Detectability with Current Methods, 2025, Journal of Artificial Intelligence Research

The scientist has collaborated extensively with other researchers, frequently coauthoring with the following individuals:

  • Kathleen Fraser
  • Isar Nejadgholi
  • Esma Balkır
  • Anna Kerkhof
  • Saif M. Mohammad

Best Publications

  • NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets

    Saif Mohammad;Svetlana Kiritchenko;Xiaodan Zhu

  • Sentiment analysis of short informal texts

    Svetlana Kiritchenko;Xiaodan Zhu;Saif M. Mohammad

  • SemEval-2016 Task 6: Detecting Stance in Tweets

    Saif Mohammad;Svetlana Kiritchenko;Parinaz Sobhani;Xiaodan Zhu

  • NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews

    Svetlana Kiritchenko;Xiaodan Zhu;Colin Cherry;Saif Mohammad

  • SemEval-2018 Task 1: Affect in Tweets

    Saif Mohammad;Felipe Bravo-Marquez;Mohammad Salameh;Svetlana Kiritchenko

  • Using Hashtags to Capture Fine Emotion Categories from Tweets

    Saif M. Mohammad;Svetlana Kiritchenko

  • Stance and Sentiment in Tweets

    Saif M. Mohammad;Parinaz Sobhani;Svetlana Kiritchenko

  • Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems

    Svetlana Kiritchenko;Saif M. Mohammad

  • Email classification with co-training

    Svetlana Kiritchenko;Stan Matwin

  • Sentiment, emotion, purpose, and style in electoral tweets

    Saif M. Mohammad;Xiaodan Zhu;Svetlana Kiritchenko;Joel Martin

  • Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010

    Berry de Bruijn;Colin Cherry;Svetlana Kiritchenko;Joel D. Martin

  • How translation alters sentiment

    Saif M. Mohammad;Mohammad Salameh;Svetlana Kiritchenko

  • ExaCT: automatic extraction of clinical trial characteristics from journal publications

    Svetlana Kiritchenko;Berry de Bruijn;Simona Carini;Joel D. Martin

  • Sentiment after Translation: A Case-Study on Arabic Social Media Posts

    Mohammad Salameh;Saif M. Mohammad;Svetlana Kiritchenko

  • Best-Worst Scaling More Reliable than Rating Scales: A Case Study on Sentiment Intensity Annotation

    Svetlana Kiritchenko;Saif M. Mohammad

  • Functional Annotation of Genes Using Hierarchical Text Categorization

    Svetlana Kiritchenko;Stan Matwin;Fazel Famili

  • NRC-Canada-2014: Recent Improvements in the Sentiment Analysis of Tweets

    Xiaodan Zhu;Svetlana Kiritchenko;Saif Mohammad

  • Learning and evaluation in the presence of class hierarchies: application to text categorization

    Svetlana Kiritchenko;Stan Matwin;Richard Nock;A. Fazel Famili

  • Detecting Stance in Tweets And Analyzing its Interaction with Sentiment

    Parinaz Sobhani;Saif M. Mohammad;Svetlana Kiritchenko

  • Capturing Reliable Fine-Grained Sentiment Associations by Crowdsourcing and Best–Worst Scaling

    Svetlana Kiritchenko;Saif M. Mohammad

  • SemEval-2015 Task 10: Sentiment Analysis in Twitter

    Sara Rosenthal;Saif M Mohammad;Preslav Nakov;Alan Ritter

Frequent Co-Authors

Saif M. Mohammad
Saif M. Mohammad National Research Council Canada
Xiaodan Zhu
Xiaodan Zhu Queen's University
Stan Matwin
Stan Matwin Dalhousie University
Colin Cherry
Colin Cherry Google (Canada)
Robert J. Coplan
Robert J. Coplan Carleton University
Veselin Stoyanov
Veselin Stoyanov Facebook (United States)
Alan Ritter
Alan Ritter Georgia Institute of Technology
Preslav Nakov
Preslav Nakov Mohamed bin Zayed University of Artificial Intelligence
Torsten Zesch
Torsten Zesch University of Hagen
Filip Ginter
Filip Ginter University of Turku

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