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Computer Science
USA
2026
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Computer Science
China
2023

D-Index & Metrics

Computer Science

D-Index
119
Citations
93275
World Ranking
149
National Ranking
87

Bing Liu 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 Bing Liu 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: 469 publications — 92nd percentile

92% of scientists in this discipline score the same or lower.

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

Bing Liu 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 Bing Liu 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: 119 D-Index — 99th percentile

99% 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

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in China Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award
  • 2016 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to data mining and development of widely used sentiment analysis, opinion spam detection, and Web mining algorithms.
  • 2015 - ACM Fellow For contributions to knowledge discovery and data mining, opinion mining, and sentiment analysis.
  • 2014 - IEEE Fellow For contributions to data mining

Overview

Bing Liu is affiliated with the University of Illinois at Chicago in the United States. Their research primarily focuses on Computer Science, with a strong emphasis on Artificial Intelligence, Information Systems, and Computer Vision and Pattern Recognition. The scientist's work also spans to Sociology and Political Science as well as Signal Processing.

The main topics covered in Bing Liu's research include:

  • Topic Modeling
  • Sentiment Analysis and Opinion Mining
  • Natural Language Processing Techniques
  • Advanced Text Analysis Techniques
  • Spam and Phishing Detection
  • Speech and Dialogue Systems
  • Text and Document Classification Technologies

The scientist has published extensively in various venues, including:

  • arXiv (Cornell University)
  • Proceedings of the International AAAI Conference on Web and Social Media
  • SSRN Electronic Journal
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Knowledge and Data Engineering

Some of the recent publications featuring Bing Liu's work are:

  • "What Yelp Fake Review Filter Might Be Doing?" (2021), Proceedings of the International AAAI Conference on Web and Social Media
  • "Exploiting Burstiness in Reviews for Review Spammer Detection" (2021), Proceedings of the International AAAI Conference on Web and Social Media
  • "Analyzing and Detecting Opinion Spam on a Large-scale Dataset via Temporal and Spatial Patterns" (2021), Proceedings of the International AAAI Conference on Web and Social Media
  • "Zero-Shot Out-of-Distribution Detection Based on the Pre-trained Model CLIP" (2022), Proceedings of the AAAI Conference on Artificial Intelligence
  • "Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning" (2021), arXiv (Cornell University)

Bing Liu is frequently collaborating with other researchers, including Sahisnu Mazumder, Lei Shu, Hu Xu, Tieyun Qian, and Arjun Mukherjee.

The scientist has also contributed to book publications, with a title published by Morgan & Claypool Publishers:

  • "Lifelong and Continual Learning Dialogue Systems" (2024)

Among their recognitions, Bing Liu was named an ACM Fellow in 2015 for contributions to knowledge discovery and data mining, opinion mining, and sentiment analysis. They were also designated an IEEE Fellow in 2014 for contributions to data mining.

Best Publications

  • Mining and summarizing customer reviews

    Minqing Hu;Bing Liu

  • Top 10 algorithms in data mining

    Xindong Wu;Vipin Kumar;J. Ross Quinlan;Joydeep Ghosh

  • Integrating classification and association rule mining

    Bing Liu;Wynne Hsu;Yiming Ma

  • Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data

    Bing Liu

  • Opinion observer: analyzing and comparing opinions on the Web

    Bing Liu;Minqing Hu;Junsheng Cheng

  • Mining opinion features in customer reviews

    Minqing Hu;Bing Liu

  • Opinion spam and analysis

    Nitin Jindal;Bing Liu

  • Deep learning for sentiment analysis: A survey

    Lei Zhang;Shuai Wang;Bing Liu

  • A Survey of Opinion Mining and Sentiment Analysis

    Bing Liu;Lei Zhang

  • A holistic lexicon-based approach to opinion mining

    Xiaowen Ding;Bing Liu;Philip S. Yu

  • Sentiment Analysis and Subjectivity

    Bing Liu

  • Opinion word expansion and target extraction through double propagation

    Guang Qiu;Bing Liu;Jiajun Bu;Chun Chen

  • Mining association rules with multiple minimum supports

    Bing Liu;Wynne Hsu;Yiming Ma

  • Sentiment Analysis and Opinion Mining.

    Lei Zhang;Bing Liu

  • Detecting product review spammers using rating behaviors

    Ee-Peng Lim;Viet-An Nguyen;Nitin Jindal;Bing Liu

  • Spotting fake reviewer groups in consumer reviews

    Arjun Mukherjee;Bing Liu;Natalie Glance

  • Sentiment Analysis: Mining Opinions, Sentiments, and Emotions

    Bing Liu

  • Building text classifiers using positive and unlabeled examples

    B. Liu;Y. Dai;X. Li;W.S. Lee

  • Mining data records in Web pages

    Bing Liu;Robert Grossman;Yanhong Zhai

  • Web data extraction based on partial tree alignment

    Yanhong Zhai;Bing Liu

  • GMC: Graph-Based Multi-View Clustering

    Hao Wang;Yan Yang;Bing Liu

  • Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data. Second Edition

    Bing Liu

Frequent Co-Authors

Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Lei Shu
Lei Shu Nanjing Agricultural University
Wynne Hsu
Wynne Hsu National University of Singapore
Xiaoli Li
Xiaoli Li Singapore University of Technology and Design
Ivet Bahar
Ivet Bahar University of Pittsburgh
P. S. Thiagarajan
P. S. Thiagarajan Harvard University
Meichun Hsu
Meichun Hsu Hewlett Packard Enterprise (United States)
Wee Sun Lee
Wee Sun Lee National University of Singapore
Rui Yan
Rui Yan Renmin University of China
Edmund M. Clarke
Edmund M. Clarke Carnegie Mellon University

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