Ph.D. Student
Brickyard Suit, 699 S Mill Ave, Tempe, AZ 85281

Google Scholar DBLP

 

News and Highlights

[8/2019] Invited to serve as a PC member for AAAI'20.

[7/2019] Our book Detecting Fake News on Social Media is online.

[6/2019] Received the student travel award for KDD'19.

[6/2019] Two papers are accepted in ASONAM'19.

[6/2019] Invited talk at Microsoft Research AI Power Lunch talk series on fake news detection.

[4/2019] One paper on "Explainable Fake News Detection" is accepted in KDD'19.

[4/2019] Our tutorial on "Fake News Research: Theories, Detection Strategies, and Open Problems" is accepted in KDD'19. See you in Anchorage, Alaska!

[3/2019] One paper on exploiting emojis for sarcasm detection got accepted at SBP.

[3/2019]I was invited to serve as a PC member in ASONAM'19, and SIGIR workshop on Reducing Online Misinformation Exposure (ROME'19).

[2/2019] Our WSDM paper on fake news detection is nicely featured in the morning paper

[2/2019] Students’ Fresh Perspectives Lead ASU Researcher to Success.

[1/2019] Invited blog post on Can AI help discern fact from fake on social media?.

[12/2018] I demonstrated FakeNewsTracker in the Global Engagement Center (GEC)'s Tech Innovation Program by the US Department of State.

 

Research Experience

  
[May 2019 - August 2019]
Research Intern at Microsoft AI Research, Redmond, WA, USA.

  
[Aug. 2015 - Present]
Research Assistant at DMML, Arizona State University, Tempe, AZ, USA.

  
[May 2018 - August 2018]
Research Intern at Yahoo! Research, Sunnyvale, CA, USA.

  
[Jul. 2014 - June 2015]
Research visiting student at ICT, Chinese Academy of Sciences, Beijing, China.

  
[Mar. 2012 - Sept. 2013]
Research Intern at HP Labs China, Beijing, China.

I am a fourth year PhD student in the Department of Computer Science and Engineering at Arizona State University, Tempe, AZ. I am a research assistant at the Data Mining and Machine Learning Lab (DMML). My advisor is Professor Huan Liu. My research lies in social computing, data mining and machine learning. My research is highly interdisciplinary and I closely collaborate with social scientists and computational journalists. My research interests are machine learning, data mining, and social media mining. Recently, I am actively working on fake news detection on social media.

Detecting Fake News on Social Media          
     Detecting Fake News on Social Media

     Morgan & Claypool Publishers, 2019

Instructor/Teaching Assistant in Fall'19    CSE 472 Social Media Mining
Office hours: Tuesday 12:00pm - 1:00pm BYE 221

 

Preprints


Tutorials

  • Fake News Research: Theories, Detection Strategies, and Open Problems.
    [PDF][Website]
    Reza Zafarani, Xinyi Zhou, Kai Shu, and Huan Liu.
    25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019).
  • Fake News: Fundamental Theories, Detection Strategies and Challenges.
    [PDF][Website][Media Coverage]
    Xinyi Zhou, Reza Zafarani, Kai Shu, and Huan Liu.
    Proceedings of 12th ACM International Conference on Web Search and Data Mining (WSDM 2019).

Books or Book Chapters

  • Studying Fake News via Network Analysis: Detection and Mitigation. [PDF]
    Kai Shu, H. Russell Bernard, and Huan Liu.
    Lecture Notes in Social Network (LNSN), Springer Press, 2018.

Journal Papers

  • Exploring Correlation Network for Cheating Detection. [PDF]
    Ping Luo, Kai Shu, Junjie Wu, Li Wan, and Yong Tan.
    ACM TIST, 2019. (Under revision)
  • FakeNewsTracker: A Tool for Fake News Collection, Detection, and Visualization. [PDF]Poster][Demo]
    Kai Shu, Deepak Mahudeswaran, and Huan Liu.
    Computational and Mathematical Organization Theory, 2019 (CMOT 2019). 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.
    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.
    SIGKDD Explorations, 2017.
  • User Identity Linkage across Online Social Networks: A Review. [PDF]
    Kai Shu, Suhang Wang, Jiliang Tang, Reza Zafarani, and Huan Liu.
    SIGKDD Explorations, 2016.

Conference Papers

    ******* 2019 *******
  • Privacy Preserving Text Representation Learning. [PDF]
    Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, and Huan Liu.
    Proceedings of the 30th ACM Conference on Hypertext and Social Media (HT 2019) (Poster paper)
  • Using Synthetic Clickbaits to Improve Prediction and Distinguish between Bot-Generated and Human-Written Headlines. [PDF]
    Thai Le, Kai Shu, Maria D. Molina, Dongwon Lee, S. Shyam Sundar, and Huan Liu.
    Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019)
  • The Role of User Profiles for Fake News Detection. [PDF]
    Kai Shu, Xinyi Zhou, Suhang Wang, Reza Zafarani, and Huan Liu.
    Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019) (Short Paper)
  • dEFEND: Explainable Fake News Detection. [PDF][Code]
    Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, and Huan Liu.
    Proceedings of 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019)
  • Exploiting Emojis for Sarcasm Detection. [PDF]
    Jayashree Subramanian*, Varun Sridharan*, Kai Shu, and Huan Liu.
    International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP 2019).
  • Unsupervised Fake News Detection on Social Media: A Generative Approach. [PDF]
    Shuo Yang, Kai Shu, Suhang Wang, Renjie Gu, Fan Wu, and Huan Liu.
    Proceedings of 33rd AAAI Conference on Artificial Intelligence (AAAI 2019).
  • Beyond News Content: The Role of Social Context for Fake News Detection.
    [PDF][Poster][The Morning Paper]
    Kai Shu, Suhang Wang, and Huan Liu.
    Proceedings of 12th ACM International Conference on Web Search and Data Mining (WSDM 2019).
  • Linked Variational AutoEncoders for Inferring Substitutable and Supplementary Items. [PDF]
    Vineeth Rakesh, Suhang Wang, Kai Shu, and Huan Liu.
    Proceedings of 12th ACM International Conference on Web Search and Data Mining (WSDM 2019).
    ******* 2018 *******
  • Deep Headline Generation for Clickbait Detection. [PDF][Slides]
    Kai Shu, Suhang Wang, Thai Le, Dongwon Lee, and Huan Liu.
    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.
    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.
    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.
    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.
    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.
    International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP 2018).
  • Personalized Privacy-Preserving Social Recommendation. [PDF]
    Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, and Yujun Zhang.
    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.
    Proceedings of 11th ACM International Conference on Web Search and Data Mining (WSDM 2018).
    ******* 2017 *******
  • 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.
    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.
    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.
    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.
    Communications and Information Processing. Springer Berlin Heidelberg, pages 246-252, 2012.
    Workshop and Demo Papers
  • dEFEND: An Explainable Fake News Detection System. [PDF][Demo]
    Limeng Cui, Kai Shu, Suhang Wang, Dongwon Lee, and Huan Liu.
    28th ACM International Conference on Information and Knowledge Management (CIKM 2019).
  • Understanding User Profiles on Social Media for Fake News Detection. [PDF]
    Kai Shu, Suhang Wang, and Huan Liu.
    1st IEEE International Workshop on Fake MultiMedia (FakeMM 2018).