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Computer Science
Germany
2023

D-Index & Metrics

Computer Science

D-Index
65
Citations
14028
World Ranking
2494
National Ranking
107

Benno Stein 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 Benno Stein 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: 373 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Benno Stein 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 Benno Stein 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: 65 D-Index — 83rd percentile

83% 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

  • 2023 - Research.com Computer Science in Germany Leader Award

Overview

Benno Stein is affiliated with Bauhaus University, Weimar in Germany and specializes in the field of computer science. Their research spans several subfields, including artificial intelligence, information systems, computer vision and pattern recognition, sociology and political science, as well as molecular biology.

The scientist's work addresses a variety of main topics, prominently featuring:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Authorship Attribution and Profiling
  • Hate Speech and Cyberbullying Detection
  • Semantic Web and Ontologies
  • Information Retrieval and Search Behavior
  • Web Data Mining and Analysis

Benno Stein has published a substantial body of work primarily in renowned venues such as Zenodo (CERN European Organization for Nuclear Research), arXiv (Cornell University), OPAL (Open@LaTrobe), ACM SIGIR Forum, and the journal it - Information Technology.

Recent notable papers include:

  • "Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models", 2022, arXiv (Cornell University)
  • "Learning Behavior Models for Hybrid Timed Systems", 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Conversational Search (Dagstuhl Seminar 19461)", 2020, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • "Identifying the Human Values behind Arguments", 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • "End-to-End Argumentation Knowledge Graph Construction", 2020, Proceedings of the AAAI Conference on Artificial Intelligence

Their collaborative network includes frequent co-authors such as Martin Potthast, Johannes Kiesel, Matthias Hagen, Henning Wachsmuth, and Maik Fröbe, reflecting an extensive engagement with peers in related research areas.

Best Publications

  • A Stylometric Inquiry into Hyperpartisan and Fake News

    Martin Potthast;Johannes Kiesel;Kevin Reinartz;Janek Bevendorff

  • The Eras and Trends of Automatic Short Answer Grading

    Steven Burrows;Iryna Gurevych;Benno Stein

  • An Evaluation Framework for Plagiarism Detection

    Martin Potthast;Benno Stein;Alberto Barrón-Cedeño;Paolo Rosso

  • Cross-Language Text Classification Using Structural Correspondence Learning

    Peter Prettenhofer;Benno Stein

  • Overview of the 2nd International Competition on Plagiarism Detection

    Martin Potthast;Alberto Barrón-Cedeño;Andreas Eiselt;Benno Stein

  • Cross-language plagiarism detection

    Martin Potthast;Alberto Barrón-Cedeño;Benno Stein;Paolo Rosso

  • Overview of the 1st international competition on plagiarism detection

    Martin Potthast;Benno Stein;Andreas Eiselt;Alberto Barrón-Cedeno

  • Intrinsic plagiarism detection

    Sven Meyer zu Eissen;Benno Stein

  • A Wikipedia-based multilingual retrieval model

    Martin Potthast;Benno Stein;Maik Anderka

  • Overview of the 5th Author Profiling Task at PAN 2017: Gender and Language Variety Identification in Twitter.

    Francisco Manuel Rangel Pardo;Paolo Rosso;Martin Potthast;Benno Stein

  • Overview of the 4th Author Profiling Task at PAN 2016: Cross-genre Evaluations

    Francisco Manuel Rangel Pardo;Paolo Rosso;Ben Verhoeven;Walter Daelemans

  • TIRA Integrated Research Architecture.

    Martin Potthast;Tim Gollub;Matti Wiegmann;Benno Stein

  • Overview of the author identification task at PAN 2014

    Efstathios Stamatatos;Walter Daelemans;Ben Verhoeven;Benno Stein

  • Automatic vandalism detection in Wikipedia

    Martin Potthast;Benno Stein;Robert Gerling

  • Intrinsic plagiarism analysis

    Benno Stein;Nedim Lipka;Peter Prettenhofer

  • SemEval 2019 Task 4 - Hyperpartisan News Detection

    Johannes Kiesel;Maria Mestre;Rishabh Shukla;Emmanuel Vincent

  • Overview of the Author Identification Task at PAN 2015.

    Efstathios Stamatatos;Walter Daelemans;Ben Verhoeven;Patrick Juola

  • Computational Argumentation Quality Assessment in Natural Language

    Henning Wachsmuth;Nona Naderi;Yufang Hou;Yonatan Bilu

  • Improving the Reproducibility of PAN’s Shared Tasks:

    Martin Potthast;Tim Gollub;Francisco Rangel;Paolo Rosso

  • Building an Argument Search Engine for the Web

    Henning Wachsmuth;Martin Potthast;Khalid Al Khatib;Yamen Ajjour

  • TL;DR: Mining Reddit to Learn Automatic Summarization

    Michael Völske;Martin Potthast;Shahbaz Syed;Benno Stein

Frequent Co-Authors

Martin Potthast
Martin Potthast Leipzig University
Henning Wachsmuth
Henning Wachsmuth University of Hannover
Paolo Rosso
Paolo Rosso Universitat Politècnica de València
Efstathios Stamatatos
Efstathios Stamatatos University of the Aegean
Gregor Engels
Gregor Engels University of Paderborn
Iryna Gurevych
Iryna Gurevych Technical University of Darmstadt
Alberto Barrón-Cedeño
Alberto Barrón-Cedeño University of Bologna
Walter Daelemans
Walter Daelemans University of Antwerp
Chris Biemann
Chris Biemann Universität Hamburg
Norbert Fuhr
Norbert Fuhr University of Duisburg-Essen

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