Wenchao Dong

Max Planck Institute for Security and Privacy

About Me

Description

Hello there! This is an e-greeting from Wenchao. I am a Ph.D. student at the Max Planck Institute for Security and Privacy (MPI-SP) in Germany, where I am advised by Meeyoung Cha and Muhammad Bilal Zafar. I received my Master’s degree from the Korea Advanced Institute of Science and Technology (KAIST) and interned at the Institute for Basic Science (IBS) in South Korea. My work has been partially supported by the Microsoft Accelerate Foundation Models Research (AFMR) initiative.

Research Interests

My research lies at the intersection of social psychology and language modeling, with a particular focus on how advances in artificial intelligence (AI) can be responsibly adopted for public benefit and how they may influence long-term societal inequalities. More concretely, I am interested in how the general public’s decision-making is being mediated by persuasive generative AI systems. I approach this through three aspects: (i) how people interact with each other through persuasive dialogues; (ii) how people delegate decision-making to agentic AI systems and are persuaded in their own choices; and (iii) whether these AI systems can themselves be persuaded when interacting with other AI systems in ways similar to humans.


Updates


Invited Talks

  • [20251028] Ethical and Regulations Challenges in the Era of LLMs @ Nanjing University, China.
  • [20241217] Factuality in the Age of LLM Biases @ WebImmunization Seminar at University of Oslo, Norway.
  • [20240909] "Ethics of AI" Can't Be Solved in a Discourse About Ethics and/or Safety @ Elkana Forum: Digital Trust in an Age of Upheaval, Germany.
  • [20240320] Persistent Out-group Bias in Large Language Models Arising from Social Identity Adoption @ Microsoft Research Asia & IBS KAIST Joint Workshop, South Korea.

Selected Publication

Description

Parallel Communities Across the Surface Web and the Dark Web
Wenchao Dong, Megha Sundriyal, Seongchan Park, Jaehong Kim, Meeyoung Cha, Tanmoy Chakraborty, Wonjae Lee
EMNLP 2025 (Findings)
Paper | Dataset

Key Findings
  • Humans have an inherent need for community belonging, which is increasingly extending into digital spaces. But how do people communicate differently between the surface web and the dark web, where communication is highly anonymous?
  • We compiled a community-matched dataset consisting of over 7 million posts and comments from Reddit and 200,000 posts and comments from Dread, a similar discussion forum on the dark web.
  • Drawing on the Sense of Community Theory, we define five aspects that measure levels of community belonging: Community Boundary, Emotional Safety, Personal Investment, Sense of Belonging, and Shared Symbol System.
  • Dread (dark web) users consistently exhibit a stronger sense of community belonging, providing more support to one another.

Get In Touch

Thanks for coming this far! I encourage you to drop me a message before you leave :)

wenchao.dong@mpi-sp.org

MPI-SP, Universitätsstraße 140, 44799 Bochum, Germany

@Wenchao_Dong