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AI scores Reddit threads by intent when Brand24 already does this.

Social listening for Reddit when Brand24 and Mention already dominate this space.
B2B marketers, SaaS founders, growth teams
Brand24 · Mention · Sprout Social
AI scores Reddit threads by intent when Brand24 already does this.
It scrapes monthly hourly 'users online' data for popular subreddits and turns it into instant per-hour, per-day charts you can use without signing up. The UI is clean and fast — search r/programming and the heatmap/bars appear — but it's essentially a tidy visualization of public counts; missing bells like timezone normalization, scheduled posting integration, or historical post-performance correlation keep it from being standout.
Nice, focused idea: paste your subreddit, title and body, get a risk score and an AI rewrite tuned for subreddit tone, plus a simple pay-as-you-go credit model. What sells it is the workflow — validate before you hit publish — but the page leaves critical questions open (how it parses Automoderator/rule text, accuracy of the risk score, and what happens to your draft data).
Uses KL divergence to give asymmetric moves the weight they deserve (a 5%→10% jump reads way louder than 50%→55%), then multiplies that by log-volume, historical SNR and trajectory consistency to surface genuinely interesting shifts. Practical engineering choices — persisted snapshots, rolling detection windows, cooldown dedupe and Telegram delivery — make this something you can drop into a trading workflow and actually rely on.
Turns noisy YouTube comments and Reddit threads into a tidy JSON: a 1–10 normalized score, plain-text summary, pros/cons, theme-level sentiment, and backlinks for provenance. Using an LLM as the extractor is clever — it sidesteps brittle selector-based scrapers — but it also raises obvious questions about cost, reliability, and how it handles sarcasm or sparse data that I'd want to see addressed.
Local feed scoring with fine-tuning, but Nitter/filter bots/feed algorithms preexist.