Mention markets are one of the most edge-rich opportunities on prediction platforms, and almost nobody is approaching them scientifically. Here's how to actually win.

What Is a Mention Market?

A mention market asks: Will Person X say Word Y in Event Z?

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It's a simple question, but winning consistently without a system is just gambling.

Step 1: Build Your Baseline (Historical Analysis)

Before any event, you need a speech fingerprint of your target.

What to collect:

• Every transcript (speeches, press conferences, debates, interviews)
• Separate by context: rallies vs. formal addresses vs. press scrums. The vocabulary is different for each event
• Note word frequency, but more importantly, trigger words, meaning phrases that appear when specific topics come up

Tools:

• Python + `pandas` for frequency analysis
• `nltk` or `spacy` for NLP
• Google Sheets if you want something simpler.

Step 2: Contextualize the Upcoming Event

Once you have the baseline, ask: What is this specific event about?

Every event has a dominant theme. That theme pulls specific vocabulary into play. Your job is to estimate the probability given the event context, and not just the historical base rate.

Framework:

P(mention) = Base Rate × Context Multiplier × Recency Weight

• Base Rate: how often does he say this word in this type of event?
• Context Multiplier: Is the topic heavily in the news right now? (If China tariffs are dominating headlines before a press conference, "tariff" probability spikes)
• Recency Weight: has he used this word in the last 7 days? People repeat what's top of mind

Example: Trump holding a rally the day after a major immigration story breaks. "Invasion" or "border" now gets a 2–3x context multiplier on its base rate.

Step 3: Find the Market Mispricing

This is where the edge lives. The market prices are based on what casual observers expect. Your pricing is based on data.

Common mispricings to hunt:

• Overpriced "signature" words: everyone knows Trump says "beautiful," so the market prices it too high. Fade these
• Underpriced topic-specific words: if a specific policy topic is breaking news but isn't famous as a "Trump word," the market sleeps on it
• Format arbitrage: the market treats all events equally. A 90-minute rally ≠ a 10-minute Oval Office address. More speaking time = higher mention probability, regardless of word

Step 4: Manage Position Sizing Like a Trader

Being right about probability doesn't mean betting everything. Use **Kelly Criterion** (or a fractional Kelly):

f = (bp - q) / b

Where `b` = odds, `p` = your estimated probability, `q` = 1 - p.

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If the market says 30% and your model says 55%, that's a strong edge, but bet fractional Kelly (25–50% of full Kelly) to account for model error.

Key rules:

• Never bet >5% of your bankroll on a single mention market
• Diversify across multiple words in the same event
• Track every bet in a spreadsheet with your estimated probability vs. the market probability

Step 5: Post-Event Review Loop

Most people skip this. It's the most important step.

After every event, log:

• What the market priced
• What your model priced
• What actually happened
• Why were you wrong (if you were)

Over 20–30 events, patterns emerge. Maybe your context multiplier is too aggressive. Maybe you're systematically underweighting rally-format events. This is how your model improves.

The Meta-Edge Nobody Talks About

The biggest edge in mention markets is timing.

Markets open mispriced and correct over time as money moves in. Getting in early, before the crowd, captures the largest spread. Monitor when markets open and be ready to move in the first 30–60 minutes before liquidity corrects the price.

Also: watch for news drops between market open and event start. A breaking story before a press conference can completely reprice a word in real time. If you're watching and the market isn't adjusting yet, that's free money.

Good luck, champ

OC: https://x.com/Predictbook/status/2056414546143633818

Polymarket has $150 WTI priced at just 2% probability,

$147 oil was a once-in-a-generation event back in 2008. However, most oil flows have more or less stabilized today. As Dyatlov said in Chernobyl:

"Not bad, not terrible."

And yet people are still extremely biased and want to be contrarian, even though they are simply wrong.

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OC: https://x.com/Predictbook/status/2056401966893281420

He turned the 2024 elections into a $22M payday, then did something almost no one in trading ever does: walked away.

Compare that to Christopher DeVocht, who transformed $60K into $400M, only to lose nearly all of it within 3 years.

The hardest skill in trading isn't finding the right trade, but it's knowing when you're done.

Looks like Theo4 figured that out early on.

https://preview.redd.it/v1xqs78r0y1h1.png?width=2196&format=png&auto=webp&s=cc8d8068fd6f9694f2b3d2d8d093805b0ca54ee2

OC: https://x.com/Predictbook/status/2056390296003387721

An attempt to build a technical "rights layer" for the AI era. A new nonprofit called RSL Media (backed by Cate Blanchett and various industry veterans) just launched the Human Consent Standard.

Unlike a simple petition or an open letter, this is a machine-readable framework designed to turn human intent into a signal that AI crawlers can actually "see" and verify.

wondering if this is a necessary piece of infrastructure for protecting creators

Source: https://x.com/unpromptednews/status/2054417527686701475

looking for an app/built in feature for a proper split for a 3 way split, any ideas?

For the past 5 consecutive weeks, Pokémon TCG RWA weekly revenue has surpassed $5M.

Weekly revenue grew from near zero in late 2023 to a consistent multi-million-dollar powerhouse in 2026.

The average Joe thinks NFTs died years ago, but in reality, some communities have found a proper use case.

This isn't a "one-day pump." It's a slow, steady grind of real users vaulting assets to gain an efficiency edge.

Yesterday's ComicBook.com x Collector Crypt announcement brings digital vending machines to a 40M-user audience on Solana, moving this from a crypto-native niche to a mainstream retail funnel.

Not a lot of media is talking about this. With AI now handling the bulk of newsroom summaries, I wouldn't expect AI to find this by scraping on-chain data, it's too busy recycling old headlines to see the real-time volume shifts.

https://preview.redd.it/volkuov2gazg1.png?width=1580&format=png&auto=webp&s=15925ba206300dc111cd950306cb491ec1d8628a

Shared it originally on X: https://x.com/TalHarelTal/status/2051583439325798442