Fan culture is becoming a differentiating variable in prediction markets

Original | Odaily (@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 prediction market development, competition revolved more around "underlying capabilities." Who is more compliant, who can gain regulatory approval, who has deeper liquidity and a more efficient market-making structure determines who can establish market trust first. Platforms represented by Polymarket and Kalshi built markets around macro politics and global major events, gradually establishing a clear cognitive advantage and user mindshare within the American context.

However, macro events themselves are not exclusive. Presidential elections, government shutdowns, war outcomes—these topics are inherently public in nature, and any platform can create similar markets. First-mover platforms rely on the accumulation of time and liquidity, not the exclusivity of the content itself. For latecomers, competing on the same topics can only be a game played on worse liquidity and weaker trust foundations, making it difficult to form a truly structural differentiation.

For emerging prediction markets on BNB Chain, if rule design cannot form a barrier, then content structure and cultural positioning might become new competitive variables. It is precisely at this stage that "fan culture" begins to become important.

Fan Culture and Exclusive Content Supply

When a prediction market platform designs events around specific ecosystems, personalities, or community hotspots, it no longer provides public issues for everyone, but rather content embedded within the context of a specific circle. For example, the 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 platform X within a week?", are essentially closer to the daily discussion rhythm of the crypto community. They may not have macro significance, but they are often at the center of the circle's sentiment.

This logic becomes more intuitive when placed in a more typical Asian fan culture scenario. For instance, whether G-Dragon's tour will add extra dates, whether Bai Lu will appear at a certain brand launch event, or whether Faker will win another championship before retiring—the appeal of such topics does not come from global attention, but from the high-density discussion within the fan circle itself. They are not public issues, but rather topic nodes with highly concentrated emotion.

Fan culture provides another motivational mechanism here. When a community is highly focused on a certain issue, participation itself becomes a way to express an attitude. Placing a bet is no longer just a probability judgment, but participation in a narrative. Compared to macro markets that require extensive information analysis, this type of topic makes it easier for people to participate directly and is more likely to drive actual trading and discussion heat in the early stages.

What is truly valuable about fan culture is not the emotion itself, but the fact that once emotion is concentrated, it naturally transforms into participation. The denser the discussion, the more active the trading, and the topic itself is continuously amplified.

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

From Communication Efficiency to Cultural Barriers

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

Discussions around macro issues typically revolve around data and analysis, with a relatively restrained pace and a more rational diffusion path. In contrast, issues centered on community figures or controversies inherently possess stronger social attributes. Conflicts of stance, expression of camps, and emotional participation make them more likely to spread rapidly on social media and within communities. In this structure, prediction markets are not just trading tools but become nodes for topic fermentation.

For emerging prediction platforms, communication efficiency itself is a growth lever. A market designed around a community controversy is often more likely to form a discussion loop than a macro-economic event. Participation, sharing, commenting, and re-participation create a reinforcing cycle; the higher the emotional density, the more concentrated the trading behavior. What fan culture brings is not just heat, but a sustainable frequency of interaction.

More importantly, when this interaction occurs over the long term within the same community context, the communication advantage gradually solidifies into a cultural bond. Currently, prediction market platforms on BNB Chain with high community discussion heat, such as Opinion, predict.fun, and Probable, have core users who themselves come from Asian communities. The concentration of the user structure naturally embeds the platform within a specific discussion environment and emotional structure.

Under such conditions, a prediction market is no longer just a replaceable trading tool, but gradually becomes part of the community's operation. Macro markets can be copied, 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.

The Asian Path Under Cultural Division

Prediction markets are not an industry where technology creates a gap; what truly determines a platform's direction is content selection and the cultural soil it binds to.

Liquidity depth, product experience, and the number of events are certainly important, but these are more like entry barriers than breakthroughs. For emerging platforms, simply copying popular events from Polymarket or Kalshi is unlikely to shake the established scale and mindshare advantages.

For a group of emerging prediction market platforms, their core users themselves come from Asian communities. The difference in user structure determines the difference in content logic. Compared to macro-political issues, Asian crypto communities place more emphasis on personality narratives, ecosystem dynamics, and community interaction. In this context, designing around community hotspots holds more practical significance than replicating public issues.

The reason fan culture is important is not because it is emotional, but because it naturally fits this user structure. It lowers the barrier to participation, increases communication efficiency, and activates real trading behavior in a short time. More crucially, this cultural soil is difficult to simply copy. Once a platform forms a bond with a specific community, the content is no longer just events, but becomes a continuously operating narrative space.

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

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

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