Original | Odaily Planet Daily（@OdailyChina）

Author | Asher（@Asher_ 0210）

Public Issues Cannot Form a Moat for Emerging Prediction Markets

The competition in prediction markets is quietly changing.

In the early stages of the development of prediction markets, competition revolved more around "underlying capabilities." Who is more compliant, who can gain regulatory recognition, who has deeper liquidity and a more efficient market-making structure, determines who can establish market trust first. Platforms represented by Polymarket and Kalshi are building markets around macro politics and major global events, gradually establishing a clear cognitive advantage and user mindset in the American context.

However, macro events themselves are not exclusive. Presidential elections, government shutdowns, and the course of wars are inherently public issues, and any platform can create similar markets. The first-mover advantage relies on the accumulation of time and liquidity, rather than the exclusivity of the content itself. For latecomers, competing on the same issues can only lead to games played on a worse liquidity and weaker trust basis, making it difficult to truly form structural differences.

For emerging prediction markets on BNB Chain, if rule design cannot create barriers, then content structure and cultural positioning may become new competitive variables. It is precisely at this stage that "fan culture" begins to gain importance.

Fan Culture and Exclusive Content Supply

When prediction market platforms design events around specific ecosystems, characters, or community hot topics, what they provide is no longer public issues for everyone but content embedded within a certain circle context. For example, related predictions launched by predict.fun around Binance ecosystem dynamics, such as "Will the SAFU fund wallet balance change?" or "How many posts will CZ make on X platform in a week?" are essentially closer to the daily discussion rhythm of the crypto community. They may not have macro significance, but they often lie at the center of community sentiment.

This logic becomes more intuitive when applied to more typical Asian fan culture scenarios. For instance, whether G-Dragon's concert will add a temporary performance, whether Baidu will appear at the launch of a certain brand, or whether Faker will win another championship before retiring, the allure of these topics does not come from global attention but from high-density discussions within the fan circles. They are not public issues but nodes of highly concentrated sentiment.

Fan culture here provides another driving mechanism. When the community is highly focused on a certain issue, participation itself becomes a way of expressing attitudes. Placing bets is no longer just a probability judgment but a narrative participation. Compared to macro markets that require a lot of information analysis, these topics are easier for people to directly engage with and can more easily drive actual trading and heated discussions in the early stages.

The true value of fan culture is not the sentiment itself but that once the sentiment is concentrated, it naturally transforms into participation. The denser the discussions, the more active the trading, and the topic itself will continue to be amplified.

This may become the biggest difference between emerging prediction markets and leading platforms. The former relies on sustained activity within circles, while the latter relies on the scale advantage of macro issues. The paths are different, and the logic is also different.

From Communication Efficiency to Cultural Barriers

Prediction markets are essentially a product driven by discussions. Without discussions, there is no price discovery; without discussions, it is difficult to form sustained participation. The platform's activity level largely depends on whether the topic can be repeatedly disseminated and amplified.

Discussions surrounding macro issues usually center around data and analysis, with a relatively restrained rhythm and a more rational diffusion path. In contrast, topics related to community figures or controversies inherently possess stronger social attributes. Position conflicts, camp expressions, and emotional participation make them easier to spread rapidly on social media and within communities. Under this structure, prediction markets do not just serve as trading tools but become nodes for topic fermentation.

For emerging prediction platforms, communication efficiency itself is a growth lever. A market designed around community controversies often forms discussion loops more easily than a macroeconomic event. Participation, reposting, commenting, and re-engagement create a cyclical reinforcement, with higher emotional density leading to more concentrated trading behaviors. What fan culture brings is not only heat but a sustainable interaction frequency.

More importantly, when this interaction occurs long-term within the same community context, the communication advantage gradually settles into a cultural binding. Current prediction market platforms on BNB Chain, such as Opinion, predict.fun, and Probable , have core users coming from Asian communities. The concentration of user structure makes the platform naturally embedded in a specific discussion environment and emotional structure.

Under such conditions, prediction markets are no longer merely an alternative trading tool but gradually become part of community operation. Macro markets can be replicated, but interaction models built within specific cultural contexts are difficult to transplant. What fan culture brings is not just short-term activity but an emotional soil that is harder for external platforms to replicate.

Asian Path Under Cultural Divides

Prediction markets are not an industry where technological differences create gaps; what truly determines the platform's direction is content choice and the cultural soil it binds to.

Depth of liquidity, product experience, and number of events are certainly important, but these are more like entry barriers rather than breakthrough points. For emerging platforms, simply replicating the hot topics from Polymarket or Kalshi is unlikely to shake the established scale and mental advantages.

A number of emerging prediction market platforms have core users from Asian communities. The difference in user structure determines the different content logic. Compared to macro political issues, Asian crypto communities emphasize narrative about figures, ecosystem dynamics, and community interaction more. In such a context, designing around community hot topics is more realistically meaningful than replicating public issues.

Fan culture is important not because it is emotional but because it naturally aligns with this user structure. It lowers participation barriers, enhances communication efficiency, and activates real trading behaviors in a short time. More critically, this cultural soil is difficult to replicate simply. Once a platform is bound to a specific community, content is no longer just about events but becomes a continuously operating narrative space.

When prediction markets enter a phase of cultural competition, what determines the platform's direction is no longer just mechanism design but the depth of understanding of its own user structure. The more someone understands their community, the more likely they are to secure a position in a differentiating landscape.

This, perhaps, is the true opportunity for emerging prediction markets.

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