World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
9632
World Ranking
11003
National Ranking
691

Diana Maynard 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 Maynard 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: 124 publications — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Diana Maynard 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 Maynard 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

Diana Maynard is a researcher affiliated with the University of Sheffield in the United Kingdom. Their work primarily spans the fields of Computer Science and Social Sciences, with a notable focus on Artificial Intelligence and Sociology and Political Science. Their research interests include misinformation and its impacts, topic modeling, spam and phishing detection, social media and politics, advanced malware detection techniques, advanced text analysis techniques, and hate speech and cyberbullying detection.

Maynard has contributed to a significant body of research that addresses various aspects of information dissemination and digital communication, particularly in the context of social media and misinformation. Their recent papers showcase a range of topics and methodologies applied within artificial intelligence and communication studies.

  • "Classification aware neural topic model for COVID-19 disinformation categorisation," 2021, PLoS ONE
  • "Using Natural Language Processing and Artificial Intelligence to Explore the Nutrition and Sustainability of Recipes and Food," 2021, Frontiers in Artificial Intelligence
  • "Similarity-Aware Multimodal Prompt Learning for fake news detection," 2023, Information Sciences
  • "Pro-Environmental Campaigns via Social Media: Analysing Awareness and Behaviour Patterns," 2020, Forschungszentrum L3S
  • "Cross-modal augmentation for few-shot multimodal fake news detection," 2025, Engineering Applications of Artificial Intelligence

Their frequent coauthors include Xingyi Song, Ye Jiang, Xiaoman Xu, Kalina Bontcheva, and Yimin Wang, reflecting collaboration across multiple interdisciplinary projects. These collaborations have contributed to a breadth of work in topics such as fake news detection, topic modeling, and social media analysis.

  • Xingyi Song
  • Ye Jiang
  • Xiaoman Xu
  • Kalina Bontcheva
  • Yimin Wang

The venues where Maynard's work has appeared include journals and conferences that focus on both artificial intelligence and social sciences. These publication outlets include arXiv, Frontiers in Artificial Intelligence, Information Sciences, Engineering Applications of Artificial Intelligence, and PLoS ONE.

  • arXiv (Cornell University)
  • Frontiers in Artificial Intelligence
  • Information Sciences
  • Engineering Applications of Artificial Intelligence
  • PLoS ONE

Their research contributions emphasize the intersection of advanced computational techniques and practical social issues such as misinformation, sustainability, and environmental awareness through digital platforms.

Best Publications

  • A framework and graphical development environment for robust NLP tools and applications.

    Hamish Cunningham;Diana Maynard;Kalina Bontcheva;Valentin Tablan

  • Text Processing with GATE

    Hamish Cunningham;Diana Maynard;Kalina Bontcheva

  • GATE: an Architecture for Development of Robust HLT applications

    Hamish Cunningham;Diana Maynard;Kalina Bontcheva;Valentin Tablan

  • The Semantic Web - ISWC 2008

    Amit P. Sheth;Steffen Staab;Michael Dean;Massimo Paolucci

  • Analysis of named entity recognition and linking for tweets

    Leon Derczynski;Diana Maynard;Giuseppe Rizzo;Giuseppe Rizzo;Marieke van Erp

  • Who cares about Sarcastic Tweets? Investigating the Impact of Sarcasm on Sentiment Analysis.

    Diana Maynard;Mark Greenwood

  • The Semantic Web - ISWC 2009

    Abraham Bernstein;David R. Karger;Tom Heath;Lee Feigenbaum

  • Automatic detection of political opinions in tweets

    Diana Maynard;Adam Funk

  • Evolving GATE to meet new challenges in language engineering

    Kalina Bontcheva;Valentin Tablan;Diana Maynard;Hamish Cunningham

  • TwitIE: An Open-Source Information Extraction Pipeline for Microblog Text

    Kalina Bontcheva;Leon Derczynski;Adam Funk;Mark Greenwood

  • Named Entity Recognition from Diverse Text Types

    Diana Maynard;Valentin Tablan;Cristian Ursu;Yorick Wilks

  • Ontology-based information extraction for business intelligence

    Horacio Saggion;Adam Funk;Diana Maynard;Kalina Bontcheva

  • Metrics for Evaluation of Ontology-based Information Extraction

    Diana Maynard;Wim Peters;Yaoyong Li

  • NLP Techniques for Term Extraction and Ontology Population

    Diana Maynard;Yaoyong Li;Wim Peters

  • Developing Language Processing Components with GATE (a User Guide)

    Hamish Cunningham;Diana Maynard;Kalina Bontcheva;Valentin Tablan

  • Architectural elements of language engineering robustness

    Diana Maynard;Valentin Tablan;Hamish Cunningham;Cristian Ursu

  • Shallow Methods for Named Entity Coreference Resolution

    Kalina Bontcheva;Marin Dimitrov;Diana Maynard;Valentin Tablan

  • Microblog-genre noise and impact on semantic annotation accuracy

    Leon Derczynski;Diana Maynard;Niraj Aswani;Kalina Bontcheva

  • Identifying terms by their family and friends

    Diana Maynard;Sophia Ananiadou

  • Proceedings of the 8th International Semantic Web Conference

    Abraham Bernstein;David R. Karger;Tom Heath;Lee Feigenbaum

  • Information Extraction: Algorithms and Prospects in a Retrieval Context Marie-Francine Moens (Katholieke Universiteit Leuven) Springer (Information retrieval series, edited by W. Bruce Croft), 2006, xiii+246 pp; ISBN 978-1-4020-4987-3, $119.00

    Diana Maynard

Frequent Co-Authors

Kalina Bontcheva
Kalina Bontcheva University of Sheffield
Hamish Cunningham
Hamish Cunningham University of Sheffield
Horacio Saggion
Horacio Saggion Pompeu Fabra University
Sophia Ananiadou
Sophia Ananiadou University of Manchester
Yorick Wilks
Yorick Wilks Florida Institute for Human and Machine Cognition
Christian Bizer
Christian Bizer University of Mannheim
Isabelle Augenstein
Isabelle Augenstein University of Copenhagen
Harith Alani
Harith Alani The Open University
Enrico Motta
Enrico Motta The Open University
Paul Baker
Paul Baker Lancaster University

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