Lab Director:

Lab Location:
Partnership 3: 2nd Floor

Lab Contact:
Yao.li@ucf.edu

The Privacy Lab explores privacy and human–computer interaction (HCI). We seek to understand users’ privacy attitudes and behaviors in their interaction with technologies and exploring how to design better systems to support users’ privacy management.

The lab applies both qualitative and quantitative methods, ranging from structural equation modeling, factor analysis, regression, longitudinal analysis, causal inference, machine learning, to grounded theory and thematic analysis.

People

  • Yao Li, Lab Director
  • Yanlai Wu, PhD student (2020-present)
  • Jing Wang, PhD student (2021-present)
  • Yifan Huang, PhD student (2023-present)

Highlights

Beyond Self-diagnosis: How a Chatbot-based Symptom Checker Should Respond
Yue You, Chun-hua Tsai, Yao Li, Fenglong Ma, Christopher Heron and Xinning Gui.
ACM Transactions on Computer-Human Interaction (accepted)

A Tale of Two Cultures: Comparing Interpersonal Information Disclosure Norms on Twitter.
Mainack Mondal, Anju Punuru, Tyng-Wen Scott Cheng, Kenneth Vargas, Chaz Gundry, Nathan S Driggs, Noah Schill, Nathaniel Carlson, Josh Bedwell, Jaden Q Lorenc, Isha Ghosh, Yao Li, Nancy Fulda, and Xinru Page.
Proceedings of the ACM on Human-Computer Interaction (CSCW 2023) (accepted).

Transparency, Fairness, and Coping: How Players Experience Moderation in Multiplayer Online Games.
Renkai Ma, Yao Li and Yubo Kou.
ACM SIGCHI Conference on Human Factors in Computing Systems (CHI 2023), Hamburg, Germany, Article 414.

Do Streamers Care About Bystanders’ Privacy? An Examination of Live Streamers’ Considerations And Strategies For Bystanders’ Privacy Management.
Yanlai Wu, Xinning Gui, Pamela J. Wisniewski, Yao Li.
Proceedings of the ACM on Human-Computer Interaction (CSCW 2023), Vol 7, No. CSCW1, Article 127.

“I Am Concerned, But…”: Streamers’ Privacy Concerns and Strategies In Live Streaming Information Disclosure.
Yanlai Wu, Yao Li, and Xinning Gui.
Proceedings of the ACM on Human-Computer Interaction (CSCW 2022), Vol 6, No. CSCW2, Article 379, 31 pages.

Privacy management in real-time information sharing
We study how people manage their privacy boundaries in synchronous multimodal information sharing, such as live streaming.

Privacy design on social media
We aim to explore better privacy design for social media users that is usable, privacy-preserving and social friendly.

Cross-cultural privacy management
We explore cultural differences in privacy attitudes and behaviors between different national cultures and privacy designs that support people to manage their privacy in different cultural context.

Research Areas:

Cybersecurity
Human-computer Interaction (HCI)
Privacy
Social Media

Capabilities & Advanced Technologies:

Equation Modeling
Machine Learning

Application Areas:

Defense
Education
Entertainment
Social Media