Story
I analyzed 571M Amazon reviews to find the most profanity-filled customer rants
1 report
1 website
1 discussion
Latest report
Overview
A Burla cluster processed 275 GB of Amazon reviews using 1,000 CPUs, categorizing them by various expressions of extreme sentiment. The system can display raw content filtered for profanity, rants, and other intense reactions.
Summary from burla-cloud.github.io.
Reports
One report so far. Additional coverage will appear here when it is linked to this story.
Community reactions
Each reaction summarizes sampled comments from the linked discussion.
Hacker News · burla-cloud.github.io
Hacker News discussion ↗
Historical count: 5 · 5 saved in sample · Historical sample
Analysis ready
Read this discussion’s reaction
Based on 5 sampled comments from this thread. Analyzed 2026-04-28.
- Praise: The creativity in the reviews showcases a unique form of expression, highlighting the diverse ways customers articulate their experiences.
- Praise: The lack of censorship in the comment section contributes to a humorous and engaging atmosphere, enhancing user interaction.
- Concern: Concerns arise about the implications of using profanity-laden reviews as training data for AI, potentially influencing model behavior in undesirable ways.