Other Possible Titles:

• 🚀 Simulating Social Bots: The Role of AI in Xiaohongshu’s Comment Ecosystem
• 🕵️‍♂️ Manufacturing Trust: Coordinated Bot Interactions on Social Media
• 🤖 Bot-Driven Credibility: Simulating Fake Endorsements on Xiaohongshu

Automated bots engage in Xiaohongshu’s comment sections, promoting ads, counterfeit products, and even services like fortune-telling. These bots evolve rapidly, constantly adapting to moderation strategies, which leads to an ongoing cat-and-mouse game with platform security systems.

1. Keyword-Based Information Extraction:
   Bots detect sensitive keywords (e.g., “shipping”, “logistics”) to target specific posts.

2. Automated Advertising & Fake Engagement:
   Bots create deceptive promotional content, sometimes posing as satisfied customers to boost credibility.

3. Coordinated Interaction for Credibility:
   Bots engage in scripted conversations to create an illusion of organic, genuine discussions.

4. The Arms Race:
   As moderation systems improve, bots adopt new evasion techniques:

   • Adversarial Content Generation: Context-aware word substitutions (e.g., "sh!pping" → "shipping")
   • Dynamic Detection Evasion: Using reinforcement learning to predict moderation updates
   • Countermeasure Adaptation: Moderation AIs employing graph-based detection and behavioral fingerprinting
   • User-AI Symbiosis: Human users inadvertently mimic bot-like patterns in their own behavior

• Sylvia LING
• Saikoro CAO
• Jay CHEN

GitHub Repo URL → https://github.com/EECS4461/Group8

We welcome contributions from the community! Here’s how you can get involved:

1. Fork this repository
2. Clone it to your local machine
3. Create a new branch for your feature or fix
4. Submit a pull request with a clear description of your changes

💡 Issues? Feel free to open one if you spot a bug or have an idea for improvement.

• Himelein-Wachowiak, M., Giorgi, S., Devoto, A., Rahman, M., Ungar, L., Schwartz, H. A., Epstein, D. H., Leggio, L., & Curtis, B. (2021). Bots and Misinformation on Social Media: A Study of Automated Behavior and Its Impact on Public Discourse.

Demonstrates pattern recognition in bot-driven misinformation campaigns

• Mena, P., Barbe, D., & Chan-Olmsted, S. (2020). Misinformation on Instagram: The impact of trusted endorsements on message credibility.

Presents GAN-based approaches for detection-evasion simulation

• Zhang, Y., Song, W., Koura, Y. H., & Su, Y. (2023). Social Bots and information propagation in social networks: Simulating cooperative and competitive interaction dynamics.

Models multi-agent adversarial dynamics in social networks

• ✅ Simulate bot behaviors and moderation strategies on Xiaohongshu
• ✅ Analyze how bots evolve to bypass content moderation
• ✅ Model the feedback loop between bot evolution and detection algorithm upgrades
• ✅ Provide insights into the effectiveness of current moderation techniques

Did you know?
Bots on social media can sometimes mimic human behavior better than real users—but they still can't decide what to eat for breakfast. 🥐☕

For updates, follow this repo and check out our commits regularly. We’re excited to share our progress and findings!