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This is a medium difficulty Analytics & Experimentation question, commonly asked during Technical Screen rounds at Meta.

What role is this question designed for?

This question is commonly asked for Data Scientist candidates at Meta during technical interviews.

Analyzing abuse in the content‑reporting system

Last updated: Mar 29, 2026

Quick 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.

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:

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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