Xinyi Zhou


Ph.D. Candidate

EECS Dept., Syracuse Univ.

[ HomeCV ]

About Me

I am a fourth-year Ph.D. candidate in Computer Science, advised by Prof. Reza Zafarani. I also closely work with Prof. Huan Liu and was a research intern at the University of Southern California, mentored by Prof. Emilio Ferrara.


My research broadly spans data (text and graph) mining, social computing, machine learning, with an emphasis on investigating information with low credibility. Currently, I am working on achieving automatic, effective, and interpretable fake news detection and intervention by incorporating domain techniques with fundamental social science theories.

To have a general idea about my research and fake news, welcome to read our paper accepted to ACM Computing Surveys (CSUR) "A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities," or see our tutorials given in WSDM'19 / KDD'19.

News & Upcoming Events

  • [May 2021] Invited to serve as a PC member of ASONAM '21.

  • [Jan. 2021] Invited to serve as a PC member of NRI-1.

  • [Dec. 2020] Invited to serve as a PC member of SIGIR '21.

  • [Nov. 2020] Invited to serve as a PC member of ECIR '21 and ROMCIR '21.

  • [Nov. 2020] I spoke with Ben Lorica of our research on fake news. Please check out Ben's podcast The Data Exchange.

  • [Oct. 2020] We released CHECKED, the first Chinese COVID-19 fake news dataset (paper, data & code). 

  • [Sep. 2020] I received SIGIR Student Travel Grant.

  • [Jul. 2020] Our paper "ReCOVery: A Multimodal Repository for COVID-19 News Credibility Research" (data & codes, slides) has been accepted to CIKM '20Thank all reviewers' positive comments.

  • [May 2020] I will intern at USC this summer mentored by Prof. Emilio Ferrara.

  • [Apr. 2020] Our survey paper on fake news research has been accepted to ACM Computing Surveys. Thank all reviewers for their constructive comments!

  • [Feb. 2020] I will give a talk on the topic of explainable fake news detection in the Applied Math Seminar at Syracuse University. Thank Prof. Minghao Rostami's invitation.  **Delayed due to COVID-19

  • [Jan. 2020] Paper "SAFE: Similarity-Aware Multimodal Fake News Detection" has been accepted to PAKDD '20 (slidescodes). We investigated how the relationship between news text and images can help detect fake news. Thank all reviewers' positive comments. 

  • [Jan. 2020] I received the Varshney Scholarship awarded to only one student in the college. Thank Alex Dunbar for the coverage.

  • [Dec. 2019] One paper was accepted as a book chapter in Lecture Notes in Social Network

  • [Dec. 2019] One paper was accepted by ACM Digital Threats: Research and Practice. In this paper, we identified the characteristics of fake news within its writing style by conducting interdisciplinary research and by comparing it with real news, deception, and clickbait. 

  • [Dec. 2019] Paper "Network-based Fake News Detection: A Pattern-driven Approach" has been available on SIGKDD Explorations. We investigated how the networks formed by news spreaders can benefit news verification.

  • [Sep. 2019] Thank Oliver Peckham for nicely featuring our KDD'19 tutorial in the article "AI Squares Off Against Fake News" on Datanami.

  • [Jul. 2019] One paper was accepted to ICWSM '20.

  • [Jun. 2019] One paper was accepted to ASONAM '19.

  • [Apr. 2019] Our tutorial collaborated with Prof. Huan Liu's team has been accepted to KDD'19. See you in Alaska!

  • [Feb. 2019] I will give a short talk in WinDS'19. See you in San Francisco!

  • [Nov. 2018] Paper "A DEMATEL-based Completion Method for Incomplete Pairwise Comparison Matrix in AHP" has been available in Annals of Operations Research. Thank Prof. Felix T. S. Chan and Prof. Alessio Ishizaka for their supports to me and this work.

  • [Nov. 2018] Two first-author papers were selected in The 100 Most Influential Research Papers in China (2017). Thank Prof. Yong Deng for his full supports to me all along.

  • [Oct. 2018] Our tutorial was accepted by WSDM'19. See you in Melbourne, Australia!