World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
23102
World Ranking
7737
National Ranking
77

Sue Moon 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 Sue Moon 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: 121 publications — 15th percentile

15% of scientists in this discipline score the same or lower.

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

Sue Moon 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 Sue Moon 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

Sue Moon is affiliated with the Korea Advanced Institute of Science and Technology in South Korea. Their research primarily spans the fields of Social Sciences and Computer Science, with notable work in the subfields of Sociology and Political Science, Information Systems, Statistical and Nonlinear Physics, Communication, and Computer Vision and Pattern Recognition.

The core topics addressed in their work include:

  • Social Media and Politics
  • Spam and Phishing Detection
  • Opinion Dynamics and Social Influence
  • Social Power and Status Dynamics
  • Digital Marketing and Social Media
  • Impact of Technology on Adolescents
  • Technology Adoption and User Behaviour

Sue Moon has contributed to several peer-reviewed publications, with a concentration in the Proceedings of the International AAAI Conference on Web and Social Media, where four papers have been published. Other venues include Communications of the ACM, KIISE Transactions on Computing Practices, The Transactions of The Korean Institute of Electrical Engineers, and Proceedings of the ACM on Networking.

Their recent papers showcase various aspects of social media dynamics and digital interactions:

  • "More of a Receiver Than a Giver: Why Do People Unfollow in Twitter?", 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "Power of Earned Advertising on Social Network Services: A Case Study of Friend Tagging on Facebook", 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "Identifying and Quantifying Coordinated Manipulation of Upvotes and Downvotes in Naver News Comments", 2020, Proceedings of the International AAAI Conference on Web and Social Media
  • "Visualizing a Personal Timeline By Adding Multiple Social Contexts", 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "Welcome", 2020, Communications of the ACM

Frequent collaborators in their research include Haewoon Kwak, Jiwan Jeong, Won-Jae Lee, Jaimie Y. Park, and Yunkyu Sohn. Moon's work often intersects with these coauthors across different projects and publications.

Best Publications

  • What is Twitter, a social network or a news media?

    Haewoon Kwak;Changhyun Lee;Hosung Park;Sue Moon

  • I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system

    Meeyoung Cha;Haewoon Kwak;Pablo Rodriguez;Yong-Yeol Ahn

  • Analysis of topological characteristics of huge online social networking services

    Yong-Yeol Ahn;Seungyeop Han;Haewoon Kwak;Sue Moon

  • Packet-level traffic measurements from the Sprint IP backbone

    C. Fraleigh;S. Moon;B. Lyles;C. Cotton

  • Measurement and modelling of the temporal dependence in packet loss

    M. Yajnik;Sue Moon;J. Kurose;D. Towsley

  • PacketShader: a GPU-accelerated software router

    Sangjin Han;Keon Jang;KyoungSoo Park;Sue Moon

  • Estimation and removal of clock skew from network delay measurements

    S.B. Moon;P. Skelly;D. Towsley

  • Analyzing the video popularity characteristics of large-scale user generated content systems

    Meeyoung Cha;Haewoon Kwak;Pablo Rodriguez;Yong-Yeol Ahn

  • Packet audio playout delay adjustment: performance bounds and algorithms

    Sue B. Moon;Jim Kurose;Don Towsley

  • Watching television over an IP network

    Meeyoung Cha;Pablo Rodriguez;Jon Crowcroft;Sue Moon

  • Prefix-preserving IP address anonymization: measurement-based security evaluation and a new cryptography-based scheme

    Jun Xu;Jinliang Fan;M.H. Ammar;S.B. Moon

  • Comparison of online social relations in volume vs interaction: a case study of cyworld

    Hyunwoo Chun;Haewoon Kwak;Young-Ho Eom;Yong-Yeol Ahn

  • The use of end-to-end multicast measurements for characterizing internal network behavior

    A. Adams;Tian Bu;T. Friedman;J. Horowitz

  • Measurement and analysis of single-hop delay on an IP backbone network

    K. Papagiannaki;S. Moon;C. Fraleigh;P. Thiran

  • SSLShader: cheap SSL acceleration with commodity processors

    Keon Jang;Sangjin Han;Seungyeop Han;Sue Moon

  • Small-time scaling behaviors of Internet backbone traffic: an empirical study

    Z.-L. Zhang;V.J. Ribeiro;S. Moon;C. Diot

  • Finding influentials based on the temporal order of information adoption in twitter

    Changhyun Lee;Haewoon Kwak;Hosung Park;Sue Moon

  • Analysis of measured single-hop delay from an operational backbone network

    K. Papagiannaki;S. Moon;C. Fraleigh;P. Thiran

  • Fragile online relationship: a first look at unfollow dynamics in twitter

    Haewoon Kwak;Hyunwoo Chun;Sue Moon

  • Analysis of point-to-point packet delay in an operational network

    B.-K. Choi;S. Moon;Zhi-Li Zhang;K. Papagiannaki

Frequent Co-Authors

Haewoon Kwak
Haewoon Kwak Indiana University
Christophe Diot
Christophe Diot Google (United States)
Meeyoung Cha
Meeyoung Cha Korea Advanced Institute of Science and Technology
Zhi-Li Zhang
Zhi-Li Zhang University of Minnesota
Hawoong Jeong
Hawoong Jeong Korea Advanced Institute of Science and Technology
Don Towsley
Don Towsley University of Massachusetts Amherst
Yong-Yeol Ahn
Yong-Yeol Ahn Indiana University
Konstantina Papagiannaki
Konstantina Papagiannaki Google (United States)
Pablo Rodriguez
Pablo Rodriguez Telefónica (Spain)
Jim Kurose
Jim Kurose University of Massachusetts Amherst

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