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D-Index & Metrics

Computer Science

D-Index
43
Citations
7497
World Ranking
8007
National Ranking
477

Arkaitz Zubiaga 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 Arkaitz Zubiaga 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: 188 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

Arkaitz Zubiaga 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 Arkaitz Zubiaga 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

Arkaitz Zubiaga is affiliated with Queen Mary University of London in the United Kingdom and specializes primarily in computer science. Their research portfolio includes 217 publications within this field, with a strong focus on artificial intelligence, which accounts for 177 of these works. Other subfields of study include sociology and political science, information systems, statistical and nonlinear physics, and computer vision and pattern recognition.

The scope of their research covers a range of topics, notably:

  • Topic Modeling
  • Hate Speech and Cyberbullying Detection
  • Misinformation and Its Impacts
  • Sentiment Analysis and Opinion Mining
  • Natural Language Processing Techniques
  • Spam and Phishing Detection
  • Advanced Text Analysis Techniques

Zubiaga's frequent publication venues reflect engagement with various academic communities. The most common platforms include:

  • arXiv (Cornell University)
  • Proceedings of the International AAAI Conference on Web and Social Media
  • PeerJ Computer Science
  • Zenodo (CERN European Organization for Nuclear Research)
  • Online Social Networks and Media

Their recent papers illustrate a sustained interest in language technologies, misinformation, and hate speech detection. Selected recent works include:

  • "Towards generalisable hate speech detection: a review on obstacles and solutions" (2021, PeerJ Computer Science)
  • "Feature-based detection of automated language models: tackling GPT-2, GPT-3 and Grover" (2021, PeerJ Computer Science)
  • "Automated fact-checking: A survey" (2021, Language and Linguistics Compass)
  • "Toward Automated Factchecking" (2021, Digital Threats Research and Practice)
  • "Online Multilingual Hate Speech Detection: Experimenting with Hindi and English Social Media" (2020, Information)

Collaboration plays a significant role in Zubiaga's research. Frequent co-authors include:

  • Maria Liakata
  • Rabab Alkhalifa
  • Aiqi Jiang
  • Elena Kochkina
  • Peiling Yi

Best Publications

  • Detection and Resolution of Rumours in Social Media: A Survey

    Arkaitz Zubiaga;Ahmet Aker;Kalina Bontcheva;Maria Liakata

  • Analysing how people orient to and spread rumours in social media by looking at conversational threads

    Arkaitz Zubiaga;Maria Liakata;Rob Procter;Geraldine Wong Sak Hoi

  • SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours

    Leon Derczynski;Kalina Bontcheva;Maria Liakata;Rob Procter

  • Exploiting Context for Rumour Detection in Social Media

    Arkaitz Zubiaga;Maria Liakata;Maria Liakata;Rob Procter;Rob Procter

  • SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours

    Genevieve Gorrell;Elena Kochkina;Maria Liakata;Ahmet Aker

  • Real-time classification of Twitter trends

    Arkaitz Zubiaga;Damiano Spina;Raquel Martínez;Víctor Fresno

  • Towards generalisable hate speech detection: a review on obstacles and solutions.

    Wenjie Yin;Arkaitz Zubiaga

  • Learning Reporting Dynamics during Breaking News for Rumour Detection in Social Media.

    Arkaitz Zubiaga;Maria Liakata;Rob Procter

  • Discourse-aware rumour stance classification in social media using sequential classifiers

    Arkaitz Zubiaga;Elena Kochkina;Elena Kochkina;Maria Liakata;Maria Liakata;Rob Procter;Rob Procter

  • All-in-one: Multi-task Learning for Rumour Verification

    Elena Kochkina;Maria Liakata;Arkaitz Zubiaga

  • Hawkes processes for continuous time sequence classification : an application to rumour stance classification in Twitter

    Michal Lukasik;P. K. Srijith;Duy Vu;Kalina Bontcheva

  • Tweet, but verify: epistemic study of information verification on Twitter

    Arkaitz Zubiaga;Heng Ji

  • A DP-based Search Using Monotone Alignments in Statistical Translation

    Christoph Tillmann;Stephan Vogel;Hermann Ney;Alex Zubiaga

  • Towards real-time summarization of scheduled events from twitter streams

    Arkaitz Zubiaga;Damiano Spina;Enrique Amigó;Julio Gonzalo

  • Classifying trending topics: a typology of conversation triggers on Twitter

    Arkaitz Zubiaga;Damiano Spina;Víctor Fresno;Raquel Martínez

  • Towards detecting rumours in social media

    Arkaitz Zubiaga;Maria Liakata;Rob Procter;Kalina Bontcheva

  • Making the Most of Tweet-Inherent Features for Social Spam Detection on Twitter

    Bo Wang;Arkaitz Zubiaga;Maria Liakata;Rob Procter

  • Stance classification in rumours as a sequential task exploiting the tree structure of social media conversations

    Arkaitz Zubiaga;Elena Kochkina;Maria Liakata;Rob Procter

  • Feature-based detection of automated language models: Tackling GPT-2, GPT-3 and Grover

    Leon Fröhling;Arkaitz Zubiaga

  • A longitudinal assessment of the persistence of twitter datasets

    Arkaitz Zubiaga

  • Enhancing Navigation on Wikipedia with Social Tags

    Arkaitz Zubiaga

Frequent Co-Authors

Maria Liakata
Maria Liakata Queen Mary University of London
Rob Procter
Rob Procter University of Warwick
Kalina Bontcheva
Kalina Bontcheva University of Sheffield
Heng Ji
Heng Ji University of Illinois at Urbana-Champaign
Trevor Cohn
Trevor Cohn University of Melbourne
Mark Rouncefield
Mark Rouncefield Lancaster University
Yulan He
Yulan He King's College London
Julio Gonzalo
Julio Gonzalo National University of Distance Education
Nicholas Diakopoulos
Nicholas Diakopoulos Northwestern University
Isabelle Augenstein
Isabelle Augenstein University of Copenhagen

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