Evaluates reporting-system analytics for valid reports and misuse detection in moderation workflows. Strong answers define distinct reported-user share, write SQL for valid reports, and detect abusive reporters through frequency, hit-rate, burst, and coordination metrics.
Scenario: Content‑reporting tools can be gamed. Calculate valid‑report ratios and detect users spamming false reports using SQL‑friendly metrics.
Question 1: Compute the share of reported users with at least one valid report. (Hint: numerator/denominator definition, deduping)
Question 2: How would you detect misuse of the reporting function? Provide metrics and SQL. (Hint: report frequency vs hit‑rate)
Quick Answer: Evaluates reporting-system analytics for valid reports and misuse detection in moderation workflows. Strong answers define distinct reported-user share, write SQL for valid reports, and detect abusive reporters through frequency, hit-rate, burst, and coordination metrics.
is_valid is defined only when moderation review is complete. Compute the share of reported users with at least one valid report and detect misuse of the reporting function.
Constraints & Assumptions
Deduplicate reported users for the share metric.
Pending reviews do not count as valid.
Reporting misuse includes frequent low-hit-rate reporting and coordinated or spammy reporting.
SQL should be clear about numerator, denominator, and time window.
Clarifying Questions to Ask Guidance
Should the denominator include users with only pending reports?
Are repeated reports for the same content or user deduped?
Is
is_valid
reliable, and how long does review take?
What action will be taken against abusive reporters?
Part 1 - Share of Reported Users with a Valid Report
Compute the share of reported users who have at least one valid report in the period.
What This Part Should Cover Guidance
Denominator: distinct reported users with at least one report in the window.
Numerator: distinct reported users with at least one reviewed and valid report.
Handle pending reviews explicitly.
Provide SQL with grouping by reported user.
Part 2 - Misuse Metrics
How would you detect misuse of the reporting function?
What This Part Should Cover Guidance
Compute reporter volume, valid-rate or hit-rate, invalid-rate, unique reported users, repeated content reports, and burstiness.
Compare reporters against peer baselines and require minimum volume before flagging.
Identify coordinated reporting and target concentration.
Include SQL focused on report frequency versus hit rate.
Part 3 - Follow-up Actions
What would you do with suspected misuse signals?
What This Part Should Cover Guidance
Use thresholds, review queues, warnings, rate limits, credibility scores, or product friction.