Bear Market Innovation: Decentralized Social Goes Social Trading with FOMO and ANTFUN Funding

BlockBeats News, June 23rd. Against the backdrop of a prolonged downturn in the crypto market, two social trading apps, FOMO and ANTFUN, successively raised funds, indicating that "decentralized social trading" is transitioning from the previous content social paradigm to a new form centered around trading relationships.

In particular, the U.S.-based crypto trading app FOMO, after receiving a $2 million seed round financing in 2025, subsequently completed a $17 million Series A funding round led by Benchmark, and a $75 million Series B funding round led by Index Ventures and Union Square Ventures, with the latest valuation at approximately $5.5 billion.

Asian social trading wallet ANTFUN, supported by Folkman Venture, mimStream, and other institutions, recently completed a $5 million strategic funding round through the AntFun Token.

Over the past few years, decentralized social experiments such as Farcaster and Lens have fundamentally migrated the traditional social models of Twitter and Medium to the chain, but they have failed to create new user behaviors, thus never producing a mass-market product.

In contrast, FOMO and ANTFUN did not rebuild a "decentralized Twitter" but built a social network around trading. Users follow real traders and friends, and their feed consists of buying and selling behavior, position changes, and profit situations, with trading records themselves becoming new social objects.

This model inherently has a business loop. User interactions, follows, and sharing orders eventually translate into trading behavior, generating revenue through fees, achieving "social for customer acquisition, trading for monetization."

In terms of product form, FOMO and ANTFUN represent two different paths: the U.S. and Asian paths. FOMO is based on an X-platform relationship network, leaning towards open public dissemination; ANTFUN relies on address books and community relationships, emphasizing private familiar networks.