Polymarket and Kaito AI Roll Out Attention-Based Markets
Attention markets shift prediction trading from outcomes to online focus, using social media data as settlement signals.
Prediction markets are starting to move past elections and price calls. Polymarket is now allowing users to trade on public attention through a new partnership with Kaito AI. These markets will track how much attention people, brands, and trends receive online, as well as public sentiment. Both companies are betting that public focus has become a meaningful indicator in a social media-driven economy.
Polymarket Turns Online Attention Into a Tradable Market
Polymarket is partnering with Kaito AI to introduce a new product type called “attention markets.” This category is tied to how much people talk about a topic online. Kaito AI will supply data sourced from platforms including X, TikTok, Instagram, and YouTube.
Using that information, the network tracks how widely a topic is discussed, known as “mindshare,” alongside the sentiment around the discussion. Polymarket will then turn those metrics into markets users can trade.
Moreover, trading volume already shows strong demand for Polymarket’s broader offering. The company’s figures show more than $3 billion in trading volume in January alone. Expansion into attention-based contracts marks a shift away from event outcomes toward tracking public focus itself.
Polymarket tested these new attention markets in November, using two small pilot markets based on Kaito AI data. One test asked how much Polymarket’s online mindshare would increase by March 31, 2026. That market has already attracted more than $1.3 million in trading volume.
Another test tracked overall crypto-related mindshare on social media and recorded about $90,000 in trades. These pilots gave traders a preview of how attention metrics could be used to decide market outcomes.
On the other hand, Polymarket’s standard yes-or-no contract model works with a similar structure. A user can buy contracts betting that a certain mindshare level will be reached by a specific date.
For example, spending $20 could buy 100 contracts predicting Polymarket’s mindshare will exceed 80%. Kaito currently estimates that figure at approximately 62%.
If the target is reached by the deadline, the contracts pay out $100. If it is not reached, the trader loses the $20 stake. Final results depend entirely on the mindshare data reported by Kaito at market close.
Kaito Positions Social Media Data at the Center of New Markets
Polymarket crypto lead Thibault said dozens of attention markets are planned for launch in early March, with hundreds expected before year-end. Early focus will remain on artificial intelligence topics, where online discussion shifts quickly and data volume remains high.
According to Kaito CEO Yu Hu, expansion into entertainment and global events is expected much later. Hu added that attention markets could change how people react to online content.
“It’ll be a completely new experience when people can scroll through social media and realize they can express their views on what they are seeing and take a side with it on these markets.”
Yu Hu said.
Many traders still struggle to understand concepts such as mindshare and sentiment, which makes early adoption more difficult. These concepts are new to most users, so trading activity may remain light initially. Kaito believes familiarity will grow with time as traders see the data used consistently and clearly.
Meanwhile, marketing teams are testing mindshare data to measure brand visibility and campaign reach. Polymarket itself had relied on Kaito’s data internally before turning it into a public product, which helped shape how the markets work.
Despite not yet fully launching in the U.S. after a federal investigation concluded last July, Polymarket continues to pursue new partnerships. Company leadership says attention markets align with a broader goal of offering tradable markets for almost anything.
The post Polymarket and Kaito AI Roll Out Attention-Based Markets appeared first on Live Bitcoin News.
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