World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
9723
World Ranking
6163
National Ranking
814

Li Chen 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 Li Chen 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: 278 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Li Chen 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 Li Chen 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: 48 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Li Chen is affiliated with Hong Kong Baptist University in China and has contributed extensively to the fields of Computer Science and Social Sciences. Their research primarily covers areas such as Artificial Intelligence, Sociology and Political Science, Information Systems, Computer Vision and Pattern Recognition, and Marketing.

The main topics explored in Li Chen's work include:

  • Recommender Systems and Techniques
  • Topic Modeling
  • Digital Marketing and Social Media
  • Privacy, Security, and Data Protection
  • Natural Language Processing Techniques
  • Advanced Text Analysis Techniques
  • Consumer Behavior in Brand Consumption and Identification

Li Chen's publication record features papers in several prominent venues. Frequently publishing in venues such as arXiv (Cornell University), SSRN Electronic Journal, ACM Transactions on Recommender Systems, User Modeling and User-Adapted Interaction, and Frontiers in Psychology, their research output spans both interdisciplinary and specialized knowledge domains.

Recent notable papers authored or co-authored by Li Chen include:

  • What drives digital engagement with sponsored videos? An investigation of video influencers' authenticity management strategies, 2022, Journal of the Academy of Marketing Science
  • Personalized Prompt Learning for Explainable Recommendation, 2023, ACM Transactions on Information Systems
  • Explainable Prediction of Medical Codes With Knowledge Graphs, 2020, Frontiers in Bioengineering and Biotechnology
  • Impacts of Personal Characteristics on User Trust in Conversational Recommender Systems, 2022, CHI Conference on Human Factors in Computing Systems
  • A grey seasonal least square support vector regression model for time series forecasting, 2020, ISA Transactions

Collaboration plays a significant role in Li Chen's research activities. Frequent co-authors include Yongfeng Zhang, Yucheng Jin, Wanling Cai, Yuhan Zhao, and Lei Li, with counts of co-authorship ranging from six to eight publications each. This network reflects engagement with diverse experts across related research fields.

Best Publications

  • A user-centric evaluation framework for recommender systems

    Pearl Pu;Li Chen;Rong Hu

  • News impact on stock price return via sentiment analysis

    Xiaodong Li;Haoran Xie;Li Chen;Jianping Wang

  • Temporal recommendation on graphs via long- and short-term preference fusion

    Liang Xiang;Quan Yuan;Shiwan Zhao;Li Chen

  • Evaluating recommender systems from the user's perspective: survey of the state of the art

    Pearl Pu;Li Chen;Rong Hu

  • Recommender systems based on user reviews: the state of the art

    Li Chen;Guanliang Chen;Feng Wang

  • A Survey on Conversational Recommender Systems

    Dietmar Jannach;Ahtsham Manzoor;Wanling Cai;Li Chen

  • Trust building with explanation interfaces

    Pearl Pu;Li Chen

  • Critiquing-based recommenders: survey and emerging trends

    Li Chen;Pearl Pu

  • Trust-inspiring explanation interfaces for recommender systems

    Pearl Pu;Li Chen

  • Survey of Preference Elicitation Methods

    Li Chen;Pearl Pu

  • GBPR: group preference based Bayesian personalized ranking for one-class collaborative filtering

    Weike Pan;Li Chen

  • Factorization vs. regularization: fusing heterogeneous social relationships in top-n recommendation

    Quan Yuan;Li Chen;Shiwan Zhao

  • Personalized Prompt Learning for Explainable Recommendation

    Unknown

  • Comparison of feature-level learning methods for mining online consumer reviews

    Li Chen;Luole Qi;Feng Wang

  • Human Decision Making and Recommender Systems

    Li Chen;Marco de Gemmis;Alexander Felfernig;Pasquale Lops

  • Personality and Recommender Systems

    Marko Tkalcic;Li Chen

  • Generate Neural Template Explanations for Recommendation

    Lei Li;Yongfeng Zhang;Li Chen

  • How Serendipity Improves User Satisfaction with Recommendations? A Large-Scale User Evaluation

    Li Chen;Yonghua Yang;Ningxia Wang;Keping Yang

  • User-Involved Preference Elicitation for Product Search and Recommender Systems

    Pearl Pu;Li Chen

  • Personalized Transformer for Explainable Recommendation

    Lei Li;Yongfeng Zhang;Li Chen

  • Prompt Distillation for Efficient LLM-based Recommendation

    Unknown

  • Generating virtual ratings from chinese reviews to augment online recommendations

    Weishi Zhang;Guiguang Ding;Li Chen;Chunping Li

  • Incorporating sentiment into tag-based user profiles and resource profiles for personalized search in folksonomy

    Haoran Xie;Xiaodong Li;Tao Wang;Raymond Y.K. Lau

  • Human decision making and recommender systems

    Anthony Jameson;MC Martijn Willemsen;Alexander Felfernig;Marco de Gemmis

Frequent Co-Authors

Pearl Pu
Pearl Pu École Polytechnique Fédérale de Lausanne
Alexander Felfernig
Alexander Felfernig Graz University of Technology
Michelle X. Zhou
Michelle X. Zhou IBM (United States)
Haoran Xie
Haoran Xie Lingnan University
Yongfeng Zhang
Yongfeng Zhang Rutgers, The State University of New Jersey
Jiming Liu
Jiming Liu Hong Kong Baptist University
Pasquale Lops
Pasquale Lops University of Bari Aldo Moro
Giovanni Semeraro
Giovanni Semeraro University of Bari Aldo Moro
Francesco Ricci
Francesco Ricci Free University of Bozen-Bolzano
Marco de Gemmis
Marco de Gemmis University of Bari Aldo Moro

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