Kai Shu  

Ph.D. Student

Department of Computer Science and Engineering
Arizona State University

Brickyard Suit, 699 S Mill Ave, Tempe, AZ 85281


[Biography] [Research Interests] [News] [Publications] [Research Experiences] [Services] [Awards]

Biography

Kai is a PhD student in the Department of Computer Science and Engineering at Arizona State University, Tempe, AZ. He also works as a research assistant at the Data Mining and Machine Learning Lab (DMML). His advisor is Professor Huan Liu. Before that, he obtained his BE in 2012 and MS in 2015 both in CS from Chongqing University, Chongqing, China. He also worked as a research visiting student in the Institute of Computing Technology, Chinese Academy of Sciences during his MS degree.


Research Interests

His research interests include data mining and machine learning, especially innovative real-world applications.


News

    [08/2018] I was interviewed by Data Skeptic, the most downloaded data related podcast on iTunes, talking about our research on fake news detection.
    [07/2018] FakeNewsTracker was awarded the Challenge Winner for the disinformation challenge in SBP 18.
    [07/2018] We released a tool FakeNewsTracker, for collecting, analyzing, and visualizing of fake news and the related dissemination on social media. Check it out!
    [03/2018] ''The data defenders'', ASU Now.
    [02/2018] I attended WSDM 2018 and gave a spotlight presentation. The datasets will be available soon!
    [10/2017] Our survey about fake news detection on social media is featured in KDNuggets!


Publication List

    Books or Book Chapters
  • Studying Fake News via Network Analysis: Detection and Mitigation. [PDF]
    Kai Shu, H. Russell Bernard, and Huan Liu.
    To appear in Lecture Notes in Computer Science (LNCS), Springer Press, 2018.
    Journal Papers
  • FakeNewsTracker: A Tool for Fake News Collection, Detection, and Visualization. [PDF]Poster][Demo]
    Kai Shu, Deepak Mahudeswaran, and Huan Liu.
    In Computational and Mathematical Organization Theory, 2018 (CMOT 2018).Best of SBP
  • Towards Privacy Preserving Social Recommendation under Personalized Privacy Settings. [PDF]
    Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, and Yujun Zhang.
    In World Wide Web Journal, 2018.
  • Fake News Detection on Social Media: A Data Mining Perspective. [PDF][Data]
    Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, and Huan Liu.
    In SIGKDD Explorations, 2017.
  • User Identity Linkage across Online Social Networks: A Review. [PDF]
    Kai Shu, Suhang Wang, Jiliang Tang, Reza Zafarani, and Huan Liu.
    In SIGKDD Explorations, 2016.
    Conference Papers
    2018
  • FakeNewsNet: A Data Repository with News Content, Social Context and Dynamic Information for Studying Fake News on Social Media. [PDF]
    Kai Shu, Deepak Mahudeswaran, Suhang Wang, Dongwon Lee, and Huan Liu.
    preprint in arXiv.
  • Deep Headline Generation for Clickbait Detection. [PDF]
    Kai Shu, Suhang Wang, Thai Le, Dongwon Lee, and Huan Liu.
    In The 2018 IEEE International Conference on Data Mining (ICDM 2018) (Regular Paper)
  • Using Social Media to Understand Cyber Attack Behavior. [PDF]
    Amy Sliva, Kai Shu, and Huan Liu.
    In 9th International Conference on Applied Human Factors and Ergonomics (AHFE 2018)
  • Exploiting User Actions for App Recommendations. [PDF][Slides]
    Kai Shu, Suhang Wang, Jiliang Tang, Yi Chang, Ping Luo, and Huan Liu.
    In The 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2018) (Short Paper)
  • Multimodal Fusion of Brain Networks with Longitudinal Couplings. [PDF]
    Wen Zhang, Kai Shu, Suhang Wang, Huan Liu, and Yalin Wang.
    In 21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018).
  • Securing Social Media User Data - An Adversarial Approach. [PDF]
    Ghazaleh Beigi, Kai Shu, Yanchao Zhang, and Huan Liu.
    In 29th ACM Conference on Hypertext and Social Media (HT 2018).
  • Understanding Cyber Attack Behaviors with Sentiment Information on Social Media. [PDF]
    Kai Shu, Amy Sliva, Justin Sampson, and Huan Liu.
    In International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP 2018).
  • Exploiting Tri-Relationship for Fake News Detection. [PDF]
    Kai Shu, Suhang Wang, and Huan Liu.
    preprint in arXiv.
  • Personalized Privacy-Preserving Social Recommendation. [PDF]
    Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, and Yujun Zhang.
    In Proceedings of 32nd AAAI Conference on Artificial Intelligence (AAAI 2018).
  • CrossFire: Cross Media Joint Friend and Item Recommendations. [PDF][Slides][Poster]
    Kai Shu, Suhang Wang, Jiliang Tang, Yilin Wang, and Huan Liu.
    In Proceedings of 11th ACM International Conference on Web Search and Data Mining (WSDM 2018).
    2017
  • Cross-Platform Emoji Interpretation: Analysis, a Solution, and Applications. [PDF]
    Fred Morstatter, Kai Shu, Suhang Wang, and Huan Liu.
    preprint in arXiv.
  • What Your Images Reveal: Exploiting Visual Contents for Point-of-Interest Recommendation. [PDF]
    Suhang Wang, Yilin Wang, Jiliang Tang, Kai Shu, Suhas Ranganath, and Huan Liu.
    In Proceedings of 26th International World Wide Web Conference (WWW 2017).
    2016
  • Multi-Label Informed Feature Selection. [PDF]
    Ling Jian, Jundong Li, Kai Shu, and Huan Liu.
    In Proceedings of 25th International Joint Conference on Artificial Intelligence (IJCAI 2016).
    Before 2016
  • Deal or Deceit: Detecting Cheating in Distribution Channels. [PDF][Slides]
    Kai Shu, Ping Luo, Li Wan, Peifeng Yin, and Linpeng Tang.
    In Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014).
  • Sequences Modeling and Analysis Based on Complex Network. [PDF]
    Li Wan, Kai Shu, and Yu Guo.
    In Communications and Information Processing. Springer Berlin Heidelberg, pages 246-252, 2012.
    Poster and Workshop Papers
  • Understanding User Profiles on Social Media for Fake News Detection. [PDF]
    Kai Shu, Suhang Wang, and Huan Liu.
    In 1st IEEE International Workshop on Fake MultiMedia (FakeMM 2018).

Research/Industry Experiences

  • Research Intern at Yahoo! Research, Sunnyvale, CA, USA. (May 2018 - August 2018)
  • Research Intern at HP Labs China, Beijing, China. (Mar. 2012 - Sept. 2013)

Services

  • Conference Reviewer: BigData'16,17
  • Journal Reviewer: TIST'18, TNNLS'18, WWWJ'18, TKDE'17, Neurocomputing'17, 18, JOCS'17
  • External Reviewer: DAMI'18, TKDE'18, SIGIR'18, ICWSM'18, PAKDD'18, AAAI'18, CIKM'17, IJCAI'16, 17, WSDM'17, ASONAM'16,17,18, RecSys'16, ICWSM'16

Awards

  • SBP Challenge Award Winner, July 2018
  • CIDSE Doctoral Fellowship Award, Arizona State University, Aug. 2015

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