Analyzing abuse in the content‑reporting system
Overview
This question evaluates data analysis and metric-design skills for product analytics in the Analytics & Experimentation domain, focusing on SQL proficiency, deduplication logic, and detection of anomalous reporting behavior in a content-reporting system.
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Jul 12, 2025, 6:59 PM
Data Scientist
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Analytics & Experimentation
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Scenario: Measuring Valid Reports and Detecting Abuse in a Reporting System
Context and Assumptions
We analyze a user reporting system to understand:
- How many reported users have at least one valid (confirmed) report.
- How to detect misuse of the reporting function (e.g., spamming false reports).
Assume a 30-day analysis window and a minimally normalized schema:
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reports(report_id, reporter_user_id, reported_user_id, content_id, created_at, is_reviewed, is_valid)
- is_reviewed: boolean indicating moderation completed.
- is_valid: boolean indicating the report was upheld/valid (only defined when is_reviewed = true).
Question 1
Compute the share of reported users who have at least one valid report in the period.
- Clarify numerator/denominator and deduping.
Question 2
How would you detect misuse of the reporting function? Propose metrics and provide SQL to compute them (focus on report frequency vs hit-rate).
Solution
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