This post offers a structured approach to answering Trust & Safety (T&S) case interview questions for a social media/user-generated content (UGC) platform.

Metadata

Inspired by the systematic methodologies in Cracking the Coding Interview and System Design Interview, this approach recognizes the importance of thinking out loud, showing your problem-solving process, and engaging in dialogue with the interviewer rather than jumping straight to a solution.

With this cheatsheet, candidates can organize their thoughts and demonstrate systems thinking under pressure.

Overview

Trust and safety decisions in social media are complex, multi-stakeholder problems that require systems thinking.

Unlike problems with binary right/wrong answers, T&S decisions involve competing values, limited resources, and consequences that extend far beyond the immediate solution.

The challenge lies in making these decisions in a legitimate, inclusive, and scalable way.

The SPIDER Method

S - Stakeholder Analysis
P - Problem Definition
I - Information Gathering
D - Decision Framework
E - Execution Planning
R - Review & Iteration

S - Stakeholder Analysis

Steps

  1. Identify All Affected Parties
    • Direct users: Those posting/consuming content
    • Community members: The broader platform ecosystem
    • Vulnerable groups: Those at risk of harm
    • Platform operators: Business and legal considerations
    • Society: Democratic discourse, public safety
    • Regulators: Legal and compliance requirements
  1. Assess Stakeholder Impact
    • Who has the most to gain/lose from this decision?
    • Which voices might not be represented in the room?
    • How do different cultural contexts affect stakeholder perspectives?
    • What power dynamics are at play?
  1. Avoid Common Pitfalls
    • Don't assume your perspective represents all users
    • Don't overlook marginalized communities
    • Don't focus only on vocal minorities
    • Don't ignore economic incentives

P - Problem Definition

Tasks

  1. Clarify the Core Issue
    • Actor: Who is involved? (Individual user, coordinated group, automated accounts, public figures)
    • Behavior: What actions are being taken? (Posting patterns, network manipulation, harassment campaigns, individual incident vs. systemic pattern, platform-specific vs. cross-platform coordination, etc.)
    • Content: What is being shared? (Text, images, links, misinformation, etc.)
  1. Assess the Scale
    • Scope: Individual (Single user/post?), Community (Specific group or hashtag), Platform (Entire service affected), Societal (Democracy, elections, public health).
    • Impact: Immediate harm vs. long-term consequences
    • Timing Considerations: How urgent is this decision? What are the consequences of delay? Is this a reactive or proactive intervention?

I - Information Gathering

Tasks

  1. Review Available Data and Signals
    • Actor analysis: Account age, verification status, follower patterns, creation methods and dates, IP addresses, device info
    • Behavioral patterns: Posting frequency, timing, network connections, automation indicators
    • Content analysis: What was actually said/shared, format, virality
  1. Understand the Precedents and Legal Requirements
    • Historical context: Previous similar cases and outcomes, how other platforms handled similar issues, what academic research suggests, what the platform has done before.
    • Obligations: What are the legal/regulatory requirements?
  1. Solicit Community Input
    • Public comment periods
    • Surveys and user research
    • Community moderator feedback
    • External expert consultation
  1. Understand our Blind Spots and Limitations
    • What constraints limit our investigation?
    • What data don't we have?
    • What trade-offs will we have to make (e.g., privacy vs. safety, time sensitivity vs. thoroughness)

D - Decision Framework

Tasks

  1. Identify Intervention options
  • Actor-Based
    • Account verification or authentication
    • Account restrictions, suspension, or termination
    • Network-level interventions (ban related accounts)
    • Privilege adjustments (reduce reach, disable features)
  • Behavior-Based
    • Rate limiting and posting restrictions
    • Algorithmic down-ranking or de-amplification
    • Requiring manual review for certain actions
    • Automated detection and flagging systems
  • Content-Based
    • Remove/label specific posts and leave tombstones/log in takedown databases (e.g., Lumen)
    • Add contextual information or fact-checks
    • Age-gate or warning screens
    • Reduce distribution without removal
  1. Identify Systemic Solutions
    • Policy updates
    • Product feature changes
    • Community tooling
    • Educational initiatives
  1. Decide on Evaluation Criteria
    • Effectiveness: Will this solve the problem?
    • Proportionality: Does the response match the harm?
    • Consistency: Aligns with previous decisions?
    • Feasibility: Can we actually implement this?
    • Legitimacy: Will stakeholders see this as fair?
  1. Decide on Trade-offs
    • Free expression vs. safety
    • Transparency vs. security
    • Individual rights vs. community protection
    • Scalability vs. nuance
    • Speed vs. accuracy

E - Execution Planning

Tasks

  1. Define Implementation Strategy
    • Technical requirements: What tools/systems are needed?
    • Human resources: Moderation team, policy experts, engineers
    • Timeline: Phased rollout vs. immediate action
    • Communication plan: Internal and external messaging
  1. Assess Resource Needs
    • Staff time and expertise required, including training
    • Technical infrastructure needs, including tooling
    • Ongoing maintenance and monitoring
    • Financial costs and budget allocation
  1. Mitigate Implementation Risks
    • What could go wrong?
    • Rollback and Backup plans, Escalation procedures
    • Monitoring for unintended consequences
    • Appeals and reversal mechanisms
  1. Define Success Metrics
    • How will you measure effectiveness?
    • Leading vs. lagging indicators
    • Quantitative and qualitative measures
    • Community feedback mechanisms

R - Review & Iteration

Tasks

  1. Monitor and Evaluate
    • Are the interventions working as intended?
    • What unintended consequences have emerged?
    • How is the community responding?
    • What new problems have been created?
  1. Set up and Integrate Feedback Loop
    • User appeals and complaints
    • Community moderator insights
    • External stakeholder input
    • Academic and journalistic analysis
  1. Identify Long-term Learning
    • What would you do differently next time?
    • How can policies/processes be improved?
    • What precedent does this set?
    • How does this inform future decisions?
  1. Improve Transparency & Accountability
    • What can be shared publicly about the decision?
    • How do you maintain trust while protecting security?
    • What documentation is needed for future reference?
    • How do you handle criticism and pushback?

Common Interview Scenarios

Scenario Types

  1. Content Moderation: Harmful posts, misinformation, harassment
  2. Account Actions: Bans, suspensions, verification
  3. Coordinated Behavior: Bot networks, astroturfing, election interference
  4. Platform Policy: New rules, enforcement guidelines, appeals processes
  5. Crisis Response: Breaking news, viral misinformation, coordinated attacks
  6. Community Governance: Decentralized moderation, user empowerment tools

Sample Questions

  • "A world leader posts content that violates platform rules. Walk me through your decision-making process."
  • "You discover a network of accounts amplifying divisive but factually accurate content. How do you respond?"
  • "A small community is experiencing targeted harassment. Design a solution that scales."
  • "Your platform is being used to organize offline violence. What do you do?"

Key Principles to Remember

  1. Start with stakeholder analysis - Don't limit yourself to the obvious personas.
  2. Think in networks, not just individuals - Behavior patterns matter more than single posts.
  3. Balance speed with legitimacy - Fast decisions aren't always good decisions.
  4. Resource constraints are real - Perfect solutions that can't be implemented don't help anyone.
  5. Transparency builds trust - But security sometimes requires confidentiality.
  6. Context matters - Different communities have different norms and needs.
  7. No decision is permanent - Build in feedback loops and iteration mechanisms.
  8. Prevention > reaction - Systemic solutions often work better than case-by-case responses.

Additional Resources to Consider

  • Study historical cases from major platforms
  • Research academic literature on online governance
  • Understand legal frameworks (Section 230, GDPR, etc.)
  • Learn from community moderation examples (Reddit, Discord)
  • Explore emerging approaches (community juries, algorithmic transparency)
  • Follow organizations like the Trust & Safety Professional Association (TSPA) and IFTAS

Remember to learn from the long history of online communities and governance experiments. The technology changes, but human behavior patterns remain remarkably consistent.