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Computer Science
UAE
2025

D-Index & Metrics

Computer Science

D-Index
76
Citations
20402
World Ranking
1356
National Ranking
12

Preslav Nakov 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 Preslav Nakov 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: 332 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Preslav Nakov 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 Preslav Nakov 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: 76 D-Index — 91st percentile

91% 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

  • 2025 - Research.com Computer Science in United Arab Emirates Leader Award
  • 2022 - Research.com Computer Science in United Arab Emirates Leader Award

Overview

Preslav Nakov is affiliated with the Mohamed bin Zayed University of Artificial Intelligence in the United Arab Emirates. Their research expertise lies primarily in computer science, with significant contributions to artificial intelligence and social sciences. The scope of their work spans multiple subfields including information systems, computer vision and pattern recognition, and communication.

The scientist has a notable record of publications focusing on various topics such as topic modeling, misinformation and its impacts, natural language processing techniques, hate speech and cyberbullying detection, spam and phishing detection, sentiment analysis and opinion mining, and multimodal machine learning applications.

Preslav Nakov's recent papers include:

  • Automated Fact-Checking for Assisting Human Fact-Checkers, 2021, Padua Research Archive (University of Padua)
  • A Survey on Stance Detection for Mis- and Disinformation Identification, 2022, Findings of the Association for Computational Linguistics: NAACL 2022
  • Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms, 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images, 2021, IRIS Research product catalog (Sapienza University of Rome)
  • On the effect of dropping layers of pre-trained transformer models, 2022, Computer Speech & Language

Frequent co-authors collaborating with Preslav Nakov are:

  • Giovanni Da San Martino
  • Firoj Alam
  • Shaden Shaar
  • Alberto Barrón-Cedeño
  • Momchil Hardalov

Their work appears regularly in various publication venues including:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • TUbilio (Technical University of Darmstadt)
  • Proceedings of the International AAAI Conference on Web and Social Media
  • Proceedings of the AAAI Conference on Artificial Intelligence

Preslav Nakov has also contributed to book publications, notably publishing with Morgan & Claypool Publishers on the title Semantic Relations Between Nominals, Second Edition in 2021.

Best Publications

  • SemEval-2017 Task 4: Sentiment Analysis in Twitter

    Sara Rosenthal;Noura Farra;Preslav Nakov

  • SemEval-2016 Task 4: Sentiment Analysis in Twitter

    Preslav Nakov;Alan Ritter;Sara Rosenthal;Fabrizio Sebastiani

  • SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations between Pairs of Nominals

    Iris Hendrickx;Su Nam Kim;Zornitsa Kozareva;Preslav Nakov

  • SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval).

    Marcos Zampieri;Shervin Malmasi;Preslav Nakov;Sara Rosenthal

  • Predicting the Type and Target of Offensive Posts in Social Media

    Marcos Zampieri;Shervin Malmasi;Preslav Nakov;Sara Rosenthal

  • SemEval-2013 Task 2: Sentiment Analysis in Twitter

    Preslav Nakov;Sara Rosenthal;Zornitsa Kozareva;Veselin Stoyanov

  • Overview of BioCreative II gene mention recognition

    Larry Smith;Lorraine K Tanabe;Rie Johnson nee Ando;Cheng-Ju Kuo

  • SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)

    Marcos Zampieri;Preslav Nakov;Sara Rosenthal;Pepa Atanasova

  • SemEval-2014 Task 9: Sentiment Analysis in Twitter

    Sara Rosenthal;Alan Ritter;Preslav Nakov;Veselin Stoyanov

  • SemEval-2015 Task 10: Sentiment Analysis in Twitter

    Sara Rosenthal;Preslav Nakov;Svetlana Kiritchenko;Saif Mohammad

  • SemEval-2017 Task 3: Community Question Answering

    Preslav Nakov;Doris Hoogeveen;Lluís Màrquez;Alessandro Moschitti

  • Fine-Grained Analysis of Propaganda in News Article

    Giovanni Da San Martino;Seunghak Yu;Alberto Barrón-Cedeño;Rostislav Petrov

  • SemEval-2007 Task 04: Classification of Semantic Relations between Nominals

    Roxana Girju;Preslav Nakov;Vivi Nastase;Stan Szpakowicz

  • Predicting Factuality of Reporting and Bias of News Media Sources

    Ramy Baly;Georgi Karadzhov;Dimitar Alexandrov;James R. Glass

  • FANG: Leveraging Social Context for Fake News Detection Using Graph Representation

    Van-Hoang Nguyen;Kazunari Sugiyama;Preslav Nakov;Min-Yen Kan

  • SemEval-2015 Task 3: Answer Selection in Community Question Answering

    Preslav Nakov;Llu'is Màrquez;Walid Magdy;Alessandro Moschitti

  • Compressing Large-Scale Transformer-Based Models: A Case Study on BERT

    Prakhar Ganesh;Yao Chen;Xin Lou;Mohammad Ali Khan

  • BioText Search Engine

    Marti A. Hearst;Anna Divoli;Harendra Guturu;Alex Ksikes

  • Proppy: Organizing the news based on their propagandistic content

    Alberto Barrón-Cedeño;Israa Jaradat;Giovanni Da San Martino;Preslav Nakov

  • SemEval-2016 Task 3: Community Question Answering

    Preslav Nakov;Lluís Màrquez;Alessandro Moschitti;Walid Magdy

  • SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles

    G. Da San Martino;A. Barrón-Cedeño;H. Wachsmuth;R. Petrov

  • SemEval-2015 Task 10: Sentiment Analysis in Twitter

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

  • SemEval-2013 Task 2: Sentiment Analysis in Twitter

    Preslav Nakov;Zornitsa Kozareva;Alan Ritter;Sara Rosenthal

  • SemEval-2014 Task 9: Sentiment Analysis in Twitter

    Sara Rosenthal;Preslav Nakov;Alan Ritter;Veselin Stoyanov

Frequent Co-Authors

Lluís Màrquez
Lluís Màrquez Amazon (United States)
Alberto Barrón-Cedeño
Alberto Barrón-Cedeño University of Bologna
Alessandro Moschitti
Alessandro Moschitti Amazon (United States)
Shafiq Joty
Shafiq Joty Salesforce (United States)
Marti A. Hearst
Marti A. Hearst University of California, Berkeley
Stan Szpakowicz
Stan Szpakowicz University of Ottawa
Jörg Tiedemann
Jörg Tiedemann University of Helsinki
Marcos Zampieri
Marcos Zampieri George Mason University
Alan Ritter
Alan Ritter Georgia Institute of Technology

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