How to research what people are really saying about a news story
Updated 23 July 2026 · by Studio Baggio
Researching a story beyond the headlines means reading the primary discussion around it: the expert threads unpacking claims, the on-the-ground reports, the pushback - and what real-money prediction markets price the outcomes at, which is often the most honest summary available.
Why the last 30 days is the window that matters
A developing story changes daily and the first version is usually wrong somewhere. The 30-day window captures the correction cycle: initial claims, pushback, verification and where consensus actually settled.
The questions worth asking
- what actually happened with [event] - expert threads
- [event] eyewitness reports
- [outcome] odds prediction markets
Where the honest signal lives
X carries the fastest primary accounts and expert unpacking, Reddit carries the aggregated timelines and fact-checking, YouTube carries the explainers, and Polymarket prices outcomes with real money - a useful antidote to hot takes.
Researching with an AI assistant? Copy this prompt
I'm researching what people actually say about a breaking story. Search recent discussion from the last 30 days across Reddit, X, YouTube, TikTok and the open web. I want: the main things people praise, the main complaints, any repeated patterns across independent threads, and a citation link for every claim. Separate strong multi-source signals from single-thread opinions.
Works in ChatGPT, Claude or Gemini - or run it in Last30Days, which does the multi-source sweep with citations built in.
Common questions
Why add prediction markets to news research?
Because odds backed by real money summarise the informed crowd's honest expectation, updated continuously. When commentary and markets disagree, that gap is itself information.
How do I avoid misinformation in fast-moving stories?
Prefer discussion that cites primary sources, watch for the correction threads that follow initial claims, and weight accounts with domain expertise over engagement bait. Cited aggregation beats any single thread.
Is this a replacement for news sites?
No - it's the layer around them: what informed discussion makes of the reporting, what's contested, and how expectations are moving.
Related research guides
Last30Days searches Reddit, X, TikTok, Instagram, YouTube, Polymarket and the open web - and cites every claim.
Try Last30Days free