In today's rapidly developing digital economy, decentralized applications are gradually penetrating various sectors, revolutionizing traditional methods of information dissemination and financial transactions. Polymarket, a blockchain-based prediction market platform, has recently gained global attention due to its unique operational model and wide-ranging applications. From predicting US election outcomes to trading information in financial markets, Polymarket has not only provided users with a platform for free expression, analysis, and information trading but has also become a bridge connecting real-world events with market sentiment. This article will explore why Polymarket has recently achieved breakthrough success and analyze the technological and social driving factors behind it.
The Decline of Traditional Media
Traditional media was once the primary channel for the public to obtain news and information. Whether through newspapers, television news, or radio, these outlets played a crucial role in shaping public opinion and political awareness. However, with the proliferation of the internet and the rise of social media, the monopoly on information has been broken.Today, emerging platforms such as social media, independent news websites, and blogs allow the public to directly access diverse perspectives rather than relying solely on a few major media institutions. This has led to a gradual decline in traditional media's authority and influence.
In recent years, the credibility of traditional media has faced increasing scrutiny. Whether due to political bias, commercial interests, or inaccurate reporting, many viewers' trust in traditional news organizations has diminished. During the 2024 election, many voters no longer relied solely on traditional news media like CNN and Fox News, instead cross-referencing multiple sources and even depending on real-time information flows from social media.
Modern audiences, especially younger generations, prefer platforms that offer real-time updates and strong interactivity. Traditional media's one-way communication model fails to meet these needs. In contrast, online platforms and prediction markets provide more dynamic interactive experiences, allowing users to directly participate in information generation and discussion.
During the 2024 US election, Vice President Kamala Harris and former President Donald Trump engaged in an intense campaign battle. Traditional media polls showed Harris's support consistently matching Trump's, with Harris even slightly leading Trump at crucial moments. Mainstream news organizations and political analysts widely predicted that Harris would defeat Trump by a narrow margin to become the first female president in US history. Some media analyses, based on voter demographics, swing state conditions, and backlash against Trump's controversial policies during his term, suggested Harris had a higher probability of winning.
However, in stark contrast to traditional media's optimistic predictions, Trump's winning probability on the prediction market Polymarket consistently remained around 60%. Despite polls showing a neck-and-neck race, Polymarket users appeared more confident in Trump's victory. This discrepancy caught the attention of many, particularly voters who were skeptical of traditional media predictions, leading them to rely more on market-driven, data-driven prediction tools.
Ultimately, as Polymarket had anticipated, Trump won the 2024 election by a significant margin. He secured 312 electoral votes, while Harris obtained only 226. This outcome not only surprised many traditional media outlets but also completely contradicted most polling institutions' predictions. Trump's performance was particularly strong in key states, especially in swing states such as Pennsylvania, Florida, and Ohio, where he successfully garnered substantial voter support, ensuring his significant lead in electoral votes.
This outcome sparked widespread discussion. First and foremost, traditional media's polling methods came under scrutiny once again. Although polls have been the primary tool for predicting election results for decades, they have repeatedly misjudged outcomes in recent years, particularly in elections involving Trump.Some analysts believe that traditional polling fails to fully reflect voters' true intentions, especially when it comes to capturing the "silent majority" or voters who are reluctant to openly express their preferences. There appears to be a structural bias in polling methodology when dealing with these segments of the electorate.Furthermore, polls typically rely on limited samples and historical data models, making it difficult to adapt to today's complex voter dynamics. This dependency on conventional methodologies has shown increasing limitations in accurately predicting modern electoral behaviors, particularly in an era marked by rapid social change and evolving political attitudes.
The Dual Nature of Polymarket: Casino and Information Source
Users predict event outcomes on the platform through betting, a mechanism very similar to gambling. In fact, many people participate in Polymarket not to gather information, but with a speculative mindset, hoping to profit from correctly predicting event outcomes. Since prediction market results are directly linked to financial stakes, these platforms can be viewed to some extent as a form of financial gambling.
A notable advantage of Polymarket lies in its ability to effectively utilize "collective wisdom" to form predictions. The theory of collective wisdom suggests that judgments from a large number of independent individuals are often more accurate than opinions from a few experts. Polymarket users come from around the world, expressing their expectations of event outcomes through financial stakes. Since users' funds are directly tied to prediction results, they tend to make decisions more cautiously. This mechanism enables Polymarket to capture the broadest range of public sentiment and expectations.
Another major advantage of prediction markets lies in their real-time nature. Traditional polls typically require days or even weeks to collect and analyze data, potentially losing some relevance in rapidly changing political environments. In contrast, Polymarket can instantly reflect market reactions to the latest information.
Whenever new election data, debates, or breaking events occur, market prices immediately fluctuate, reflecting users' interpretations and expectations of this information. This real-time response provides observers with prediction data much faster than traditional media.
Polymarket's price movements also offer analysts deeper insights. By observing market trends, analysts can understand how public perceptions of specific events change over time. This dynamic prediction capability provides a new tool for political analysis and election forecasting, enabling observers to respond more flexibly to changes in electoral situations.
The platform's ability to capture immediate market sentiment and translate it into quantifiable data represents a significant advancement in political forecasting methodology. This real-time feedback loop between events and market reactions provides a more nuanced and dynamic understanding of political developments compared to traditional polling methods.
Information Finance and Prediction Markets
From an information finance perspective, financial markets function as multidimensional systems for information processing and value discovery. These systems, through complex pricing mechanisms, not only integrate and reflect traditional supply and demand information but also capture and transmit signals of various social, economic, political, and even environmental changes. Specifically, when market participants trade based on their information and analysis, they are participating in a vast information game: institutional investors may make decisions based on detailed fundamental research, hedge funds might capture market anomalies through complex quantitative models, while individual investors might invest based on their observations and judgments of industry trends. This diverse information from different levels and dimensions gets encoded into prices through trading activities, making market prices a comprehensive indicator containing massive amounts of information.
Looking further, this information integration mechanism has spawned many innovative financial tools and markets: prediction markets aggregate expectations about elections, policy impacts, and technological developments; weather derivative markets reflect climate change risk assessments; credit default swaps contain market judgments about corporate credit conditions. These innovations not only enrich financial market functions but also provide society with new channels for information acquisition. The concept of information finance is driving financial markets to evolve into more efficient information processing platforms. The application of blockchain technology has made information transmission more transparent and traceable, while developments in big data and artificial intelligence have enhanced markets' information processing capabilities. The rise of social media has also injected new information sources into markets.
According to Vitalik's article "From prediction markets to info finance" published on November 9, 2024, information finance as an innovative three-sided market model cleverly connects predictors (bettors), information users (readers), and market platforms. Its uniqueness lies in that it's not just a simple information exchange platform, but a mechanism specifically designed to generate and transmit predictive information. Through market participants' betting behavior, it integrates dispersed judgments and predictions into valuable information products and outputs them as public goods to a broader audience. This design both ensures prediction quality (through economic incentives) and maximizes the social value of information (through public good properties), demonstrating the enormous potential of financial innovation in information production and transmission.
He believes that with AI development, many key pain points of low-volume small prediction markets will be resolved. Traditional small prediction markets face a fundamental contradiction: low trading volume makes it difficult to recover professional analysis costs, and lack of sufficient market participants makes price discovery mechanisms ineffective. The introduction of AI technology will fundamentally change this situation: it can conduct in-depth analysis at extremely low costs, generating high-quality prediction information even in micro-markets with only $10 in trading volume. This means information finance can expand to millions of small decision-making domains, greatly extending its application scope. Even in cases requiring market subsidies, AI participation will significantly reduce the operating costs per prediction problem, making large-scale deployment of micro prediction markets economically feasible. This transformation will allow information finance to truly realize its potential as a distributed information processing system, providing broader and more detailed information support for social decision-making.
Meanwhile, Vitalik proposed an ingenious mechanism design to "refine" high-cost but reliable judgment mechanisms through prediction markets. The core idea is to have market participants predict what expensive original mechanisms would judge, and only actually trigger the original mechanism for verification in extremely rare cases (0.01%). Through economic incentives, accurate predictors profit while incorrect predictors lose, making this low-cost "refined version" gradually approach the judgment quality of the original mechanism. This design maintains both credibility and neutrality while significantly improving efficiency and scalability, providing an innovative solution for social decision systems (such as DAO governance) and cleverly resolving the traditional contradiction between credibility and efficiency.
Summary
This article deeply explores how Polymarket as a prediction market platform stood out in the 2024 US election and demonstrates its significance in information finance innovation. By analyzing the limitations of traditional media and using the example of Polymarket accurately predicting Trump's victory over Harris, the article reveals the unique advantages of prediction markets compared to traditional polls. It also discusses in detail Polymarket's dual nature as both casino and information source, emphasizing its innovations in information dissemination through collective wisdom and real-time response. Combined with Vitalik's latest theoretical perspectives, the article further explores the future development of information finance, particularly AI technology's role in driving micro prediction markets, and how innovative "refinement mechanisms" provide new solutions for social decision systems while maintaining credibility and improving efficiency. This innovation not only changes traditional information acquisition models but also creates a new paradigm for financial markets in information processing and value discovery.
