Introduction

One of the most pressing issues in today’s society is the prevalence of a multitude of “talking heads,” opinion leaders, and interested parties who provide opinions and interpretations of reality. These voices fragment the truth, making it highly relative and, crucially, practically unverifiable for us, consumers of social reality. It is extremely challenging for us to distinguish valuable assessments from the plethora of fragmented and often opposing viewpoints since we cannot verify their accuracy, authority, or impartiality.

One theoretical solution to this problem is the introduction of a so-called social rating system or trust rating. However, as evidenced by authoritarian states’ practices, such a rating system merely shifts the same problem to a higher level of abstraction. This occurs either due to the lack of transparency in such a rating system’s mechanism or due to the emergence of “enclaves of opinions” — closed systems of views that do not accept external assessments due to the conformist nature of their formation.

The emergence of public, open, and decentralized blockchains and the social technologies that have emerged thanks to them have opened up another path to addressing the issue of unverifiable social reality.

A specific example of such a solution can be found in entities never seen before in the 21st century, referred to as “on-chain whales”.

On-chain whales are wallets that hold large sums of assets and conduct their trading and investment activities on public blockchains.

If in the past, to discover which securities and in what quantities an investment firm purchased, we had to wait for the publication of their quarterly report, now we can see a transaction made by an on-chain whale seconds after its completion. We might not even know the individual or group that owns the private keys to the wallet. However, what is essential is that this wallet has a verifiable history of its financial successes and failures. Such a wallet “votes” not with its “voiced opinions in media resources” but with its own funds. The owners of these wallets take on the risk, meaning they are responsible for their evaluations, which they bear primarily, and nobody else.

Nevertheless, you might ask, how is this related to social reality? That some whales buy digital assets and can provide hints to “on-chain hunters” is long known.

What relevance do these assets have to assessing social phenomena and events?

Direct relevance, indeed. Public programmable blockchains, as a rapidly evolving social technology, already allow trading not only assets but also predictions on the outcome of various real-world events. In a sense, any real-world event can be “tokenized” and converted into the status of a financial asset until its logical resolution. The most classic example of such an event is the US presidential elections. For several years now, anyone can vote for a candidate, even if they are not a US citizen, not yet 21 years old, or if the elections have not officially begun. Furthermore, they can earn from it. All that needs to be done is to use any of the decentralized prediction markets available today. As soon as anyone can profit from this, it inevitably creates the space and conditions for creating an “efficient” market. In other words, a market where authors aim to maximize their profits by finding a common balance in the equilibrium price or, in our case, the “equilibrium probability” of a particular event. Here is your social technology — a decentralized betting game on real-world event outcomes that leads to a market valuation of the probabilities of these outcomes, which can be verified with a “stake,” or capital, from those who vote.

Prediction Markets Before Ethereum. Liquidity Problem.

Before delving into the technical aspects of on-chain prediction markets, it is essential to provide some historical context.

Prediction markets existed before the emergence of public blockchains. The Iowa Electronic Markets (IEM) is the first and most well-known platform for prediction markets. It is classified as nonprofit because it was established as an educational and motivational tool for students at the University of Iowa. Initially, IEM allowed students to invest real money and trade “shares” of political candidates or parties. Over time, they added markets related to economic indicators, quarterly company earnings, stock performance, and box office revenues for movies.

Although IEM still exists today and has even served as the basis for research confirming the high accuracy of such predictions compared to standard pre-election polls, it has a significant limitation that hinders it from becoming highly liquid and popular. Due to its nonprofit (research-oriented) nature, the maximum bet size for users is limited to $500. Additionally, as mentioned earlier, it only offers markets related to electoral events in the United States, which is not as relevant for residents of other countries.

The most popular off-chain prediction markets at the moment are PredictIt and Manifold. PredictIt, again, restricts users to a relatively small set of markets related to political events in the United States. In contrast, Manifold has a broader range of markets. Nevertheless, Manifold still faces the most critical problem for prediction markets — low liquidity. Making bets as small as $100 can shift the market balance significantly against users, essentially making it more of a game than a viable method for speculation (earning).

Prediction Markets After Ethereum. Betting on the Rise.

On February 18, 2021, Vitalik Buterin published a blog post titled “Prediction Markets: Tales from the Election”. In this post, Vitalik summarizes the issues with existing off-chain prediction markets and contrasts them with the potential of blockchain-based prediction markets:

In brief, prediction markets (not related to blockchain) that most people used until at least 2020 had various limitations that made it difficult for users with small amounts of money to participate. If a smart person or professional organization noticed that the market was pointing in the wrong direction, it would be very challenging for them to redirect prices in a way that they considered favorable.

…perhaps prediction markets of the old format with their inflexibility and centralization indeed have low limitations and high commissions. But crypto markets are immune to this! Augur or Omen [current prediction markets at that time, though later lost competition — author’s note] do not impose limits on how many tokens one can buy or sell for a specific outcome if they believe the prices are undervalued or overvalued. However, prices on blockchain prediction markets did not differ significantly from prices on PredictIt.

In conclusion, Vitalik characterizes his evaluation of prediction markets as highly optimistic and presents arguments in favor of their future development. These arguments boil down to the idea that such markets will enable users who understand specific social domains to monetize their experience and knowledge. Additionally, technological scaling solutions will improve the UX/UI design of these markets and reduce user fees. He also mentions that the mere existence of such markets over time will prove their reliability, alleviating concerns of potential participants. Ultimately, he hopes that the technology of prediction markets will improve, and he offers his vision for a market design that could enhance the efficiency of simultaneous bets on many unlikely events, helping to prevent irrationally high odds on improbable outcomes.

Now, nearly three years later, after being encouraged by Vitalik’s insights, we can examine the current state of blockchain-based prediction markets.

Polymarket — The Undisputed Leader in Prediction Markets

The most liquid and well-known platform is the decentralized application Polymarket, operating on the Polygon network (an Ethereum sidechain). As of today, the total value locked (TVL) in accordance with DefiLlama’s data amounts to $8.5 million.

The platform itself comprises a multitude of markets, each of which represents a clearly formulated question with at least two possible answers: “Yes” and “No.” This question must always imply a specific date for its “closing,” signifying the event’s outcome in favor of either a positive (“Yes”) or negative (“No”) result. Any user can deposit their USDC tokens onto the platform and purchase “shares” representing their votes. The price of these shares is determined by the market mechanism (supply and demand balance) and is always within the range of $0 (market evaluates the probability as 0%) to $1 (market evaluates the probability as 100%).

This allows users to compare the current market share prices with their own probability assessment of the event. When the event expiration date arrives, the prediction market closes. All shares held by users who made accurate predictions become worth $1, while all shares owned by users who bet incorrectly become worth $0. An essential nuance is that the shares purchased by users remain tradable throughout the market’s operation until its closure (expiration). This means users are not obliged to wait until the expiration date and are free to sell their shares at any time at the current market price when they intend to sell their votes. A common type of market consists of two possible event outcomes.

As seen in the current market “Will Putin be the President of Russia until the end of 2023,” the price of “Yes” shares was $0.94 at the end of October, while the price of “No” shares was $0.07. This implies that the market assesses the probability of a positive outcome for this event as 94% and a negative outcome as 7%. It’s important to note that the total sum of these probabilities exceeds 100% (101% in this case), which Polymarket explains as follows: “Minor shifts occur due to market uncertainty and other price factors.”

Pay attention to the fact that the price of “No” shares reached $0.35 at its peak overnight from June 23 to June 24. This indicates that participants in this market estimated the success of the Wagner Group rebellion at around 35%. Users who recognized the market’s overvaluation of the negative outcome for the government could buy “Yes” shares for $0.65 and earn around 50% in a week by selling these shares for $0.9 when the market returned to assessing a 90% probability of the safety of the Russian President’s position.

For those familiar with derivative financial instruments such as options, prediction markets exhibit similar elements. Indeed, as we know, purchasing call/put options grants us the right to buy/sell the underlying asset at the option’s strike price before its expiration date. We must pay a market premium for this right, which is the option’s cost, and the size of this premium limits our risk for the position. In case the price of the underlying asset doesn’t move in our favor, we will only lose the funds spent on acquiring this right, which is the option’s cost (premium). Prediction markets operate in the same way, except that the expiration date is not tied to the end of a specific quarter, as is customary in classical options, but to any date relevant to a particular event. Importantly, this expiration date can be shifted in case the event does not occur, as recently happened in the prediction market regarding the results of the presidential elections in Argentina.

The initial expiration date — October 22 — corresponded to the election date, but the pool’s description stated: “This market includes any potential second round of voting.” This is exactly what happened in reality, and now this market continues to operate until the second round date, which is November 19.

By the way, we can see how abruptly this market reevaluated Javier Milei’s chances for the presidency on October 23 after the first-round results were announced. By the end of October, it estimates his chances at 32% against Sergio Massa’s 69%.

The most significant distinguishing feature of Polymarket from the prediction markets mentioned in the previous paragraph (IEM, PredictIt, Manifold) is the fact that the liquidity depth of Polymarket’s markets is orders of magnitude higher than its off-chain counterparts. In the example of the market about Putin’s presidency, the total bet size in the market is $447,000. A new bet of $10,000 won’t be able to shift the average share purchase price even by $0.1! Many Uniswap pools would envy such a low “slippage.”

High liquidity depth is not only interesting for speculation but also because the higher it is, the more we can rely on the market’s effective assessment of the event’s outcome. Below, we’ll provide an overview of some interesting ongoing Polymarket markets, which offer us insights into certain aspects of social reality from a market perspective.

• Who will be the Republican Party’s candidate in the U.S. in 2024?
  Answer: Donald Trump, probability 81%
  Total bet size in the market: $5.14 million
• Who will be the Democratic Party’s candidate in the U.S. in 2024?
  Answer: Joe Biden, probability 75%
  Total bet size in the market: $3 million
• How much will global warming be in 2023?
  Answer: More than 1.05 degrees Celsius
  Total bet size in the market: $688,000

You can see that prediction markets use many terms and mechanics from traditional financial markets: prices, liquidity depth, slippage, market premiums, risk/reward. And what if we told you that arbitrage opportunities also exist in these markets?

Look at this Polymarket market: “Will Joe Biden be the President of the United States on December 1 (or February 1), 2024?”
Answer: Yes, probability 99%
Total bet size: $3 million

Now, take a look at this market opened on another on-chain prediction market platform. The formulated question sounds almost the same: “Biden, U.S. President until the end of 2023?”, but the probability here is evaluated differently by the participants:
Yes = 2.63x
No = 1.61x

Even though the probability here is not expressed in the range from 0 to 1 but in coefficients, similar to those on betting platforms, it’s clear that the participants in this market assess the reliability of Biden’s positions significantly lower (around 40%).

Thus, an arbitrage opportunity arises, characterized by an asymmetry in risk and reward: you can buy “No” on the first market and “Yes” on the second and still come out ahead in any case, right? Well, before you rush to buy opposing shares on these platforms, it’s worth discussing the risks.

HILO — a dark horse with unicorn tendencies

So, what is HILO? The very name of the application is an abbreviation of High + Low, hinting at its strong resemblance to binary options mechanics.

Binary options are markets where traders can bet on whether an asset will go up or down over a specific period (usually extremely short, sometimes as little as 1–2 seconds).

Binary options themselves have a bad reputation and are more associated with pure gambling than trading. However, we are interested in HILO as a protocol that provides prediction market services.

The protocol offers two types of pools:

1. Classic binary options on meme coins (price predictions).
2. Prediction markets for real-life events (real-life predictions).

Currently, the most liquid pools related to politics include:

• “Will the SEC approve BlackRock’s spot ETF application in 2023?”
  Yes = 1.47x (70%)
  No = 3.14x (30%)
• “Will Elon Max become the richest person on Forbes’ list by the end of 2023?”
  Yes = 1.36x (75%)
  No = 3.81x (25%)
• The pool mentioned earlier, “Will Biden remain in office until the end of 2023?”
  Yes = 2.63x (40%)
  No = 1.61x (60%)

The platform claims on its analytical dashboard that the total bet size at the moment is $11 million in USD terms. However, we cannot verify this as the protocol does not have a page on Dune Analytics.

HILO prediction markets have two key differences from Polymarket:

1. Bets are only accepted in the native HILO token. Users cannot deposit stablecoins or ETH into the protocol’s pools, exposing users to the risk of devaluation of their bet in USD terms, even if they win.
2. Once a bet is made, users cannot exit it until the pool’s expiration date, making their funds illiquid for the pool’s duration, which increases the risk of devaluation of their bet.

It seems that these reasons are contributing to the inefficiencies we see in HILO pools compared to Polymarket markets. It’s worth noting that the market has experienced a rapid revaluation of the HILO token’s value over the past few months: the token’s price has increased by 8200% from its low in July 2023 to its peak in October 2023, and it is currently trading at around $0.24, which corresponds to a market capitalization of around $24 million.

This growth is likely caused by the strict utility of the token itself, as users have no other option to place a bet except to buy the platform’s token. It creates an unusual and somewhat paradoxical situation: the positive price dynamics of the protocol’s token create difficulties in attracting TVL to the protocol itself because, as it seems to us, a small number of participants will risk buying a token that has skyrocketed in price by more than 50 times in a short period. Nevertheless, we must acknowledge the significant attention speculators are paying to this platform, creating a foundation for the emergence of other protocols involving the token in the mechanics of their prediction markets.

Looking to the Future

Imagine a world where news briefs are accompanied not only by the opinions of analysts and commentators but also by dashboards with information about prediction markets relevant to the news. You can verify them on-chain, similar to how it works on Dune Analytics. In these dashboards, you can see how market participants (just like you, members of social reality) assess the probability of different outcomes of these events. You also see an “efficiency” parameter for the estimation of this probability, which is directly proportional to the depth of liquidity, i.e., the total number of bets on this event.

Wouldn’t it be much easier to navigate in an information flow presented in this way? The complex, seemingly almost unpredictable terrain of social reality would become clear. And even if most people make mistakes at some point, as these mistakes are discovered, the balance of probabilities shifts (dynamic balance of supply and demand). Moreover, if the success of your business or previously made investment decisions depends on certain events, you would have the opportunity to hedge these risks by purchasing shares in an undesirable outcome! For example, imagine that you invested a large sum in opening a restaurant at the end of 2019 and, by the beginning of 2020, you receive more and more news about the risk of a global epidemic. If on-chain prediction markets were already widespread at that time, you would have the opportunity to invest some of your funds in a bet on stricter quarantine measures in your country or other negative consequences of the epidemic, thereby allowing you to reduce the overall losses from the occurrence of such consequences.

Certainly, all of this sounds highly utopian and, for some, even dystopian, as it’s possible to imagine that in such a system, “bad actors” could emerge, capable of manipulating events for profit due to their political or financial resources. However, it’s important not to underestimate the possibilities and perspectives offered by social technologies. They can offer us new mechanisms of checks and balances, such as decentralized governance, quadratic voting, and more…

Stay tuned.

Sources:

• https://medium.com/r/?url=https%3A%2F%2Fen.wikipedia.org%2Fwiki%2FSocial_Credit_System
• https://www.sciencedirect.com/science/article/abs/pii/S0169207008000320
• https://vitalik.ca/general/2021/02/18/election.html
• https://ethresear.ch/t/prediction-market-design-for-betting-on-many-highly-improbable-events/8280
• https://defillama.com/protocol/polymarket
• https://en.wikipedia.org/wiki/Wagner_Group_rebellion
• https://medium.com/r/?url=https%3A%2F%2Fwww.investopedia.com%2Fterms%2Fs%2Fslippage.asp

Links

Website — https://y2.finance/
Twitter —https://x.com/ytwofund

Abstract

In this article, we delve into the realm of social tokens, tracing their history from the advent of social tokens and bonds tied to the identities of well-known individuals to the primary challenges faced by the target audiences of these celebrities. We conduct a competitive analysis of a sample of 22 projects, explore the genesis of key issues despite the exponential growth of the creator sphere, and propose hypotheses for problem resolution. Through this article, you will gain insights into how the social token ecosystem operates, which projects are viable for investment, and how to analyze them.

The History of the Creator Sphere and the Emergence of the “Influence Bubble”

As media evolved, celebrities gained widespread access to their audience. The advent of the internet in the 1990s opened up new possibilities for them through platforms like Twitter, YouTube, and Instagram. The interaction between celebrities and their fans became easier than ever, giving rise to a new generation of famous personalities known as influencers. These individuals garnered popularity through their online presence and their ability to engage with their fan base.

Just 15 years ago, celebrities led lives not much different from the average person. However, today, influencers are reaping substantial profits from social media platforms. This transformation has influenced the quality of content, enabling bloggers to invest millions in creating high-quality videos.

The Marketing Gold Rush Concept

The concept of the “marketing gold rush” emerged in the early 2000s as marketers faced challenges in targeting the demographic of individuals aged 18 to 35. With the advent of social media, they found a solution: influencer marketing. Advertising through bloggers cost significantly less than traditional television advertising.

For example, to reach 100 million users through advertising, companies could pay just over $100,000, whereas achieving the same goal through television would cost millions of dollars.

Over time, the cost of influencer marketing reached an equilibrium with television advertising, but the trust in bloggers remained high. However, many companies could not afford this type of advertising due to the substantial risks involved.

However, as influencers began endorsing products without always fully understanding or aligning with the products they promoted, people started to trust them less. This trust issue became a critical factor affecting conversion rates, leading to what we now know as the “Influence Bubble”.

Reasons of the “Influence Bubble” Emergence

If we consider the establishment of equilibrium, we can understand that monetization itself led to the problem of distrust. Influencers increased their fees for advertising, improving their own lifestyles, while their followers remained relatively unchanged, causing a disconnect. Additionally, as influencers did not verify or anticipate their audience’s reactions to various advertisements, audience trust began to erode. While the first point can be seen as a natural outcome of celebrity development, the second point is a direct problem related to monetization.

Ways to Monetize an Audience

Influencers can monetize their activities in several ways:

1. Developing their own brand of products, such as clothing or accessories.
2. Advertising contracts for promoting brands on social media.
3. Sponsorships and partnerships with brands.
4. Subscriptions — services where fans can purchase access to specific content.
5. Hosting events and workshops.

Essentially, sponsorship, partnership (affiliate marketing), and advertising are fundamentally forms of monetization. The fifth point may not be suitable for most celebrities due to the nature of their content or obstacles related to their target audience, which will be discussed later.

As discussed earlier, issues with advertising lead to a loss of trust in the influencer and can jeopardize their career. Hosting events may not be suitable for all influencers, as their audience may be geographically dispersed, and influencers focused on producing funny and silly content may not be able to organize workshops — at most, they can engage in fan meet-ups. This leaves subscriptions for paid content.

In other words, to improve their monetization methods, influencers need to transition to a new level of interaction with their subscribers. In the best-case scenario, celebrities will maintain a balance of trust with their audience while continuing to earn from this field, avoiding the risk of alienating their audience.

Just as in the 2000s when media helped influencers transition to a new level of communication and engagement with their target audience, there is a pressing need for a new transition today.

However, as influencers transition to this format of communication and improve their connection with their audience, they quickly encounter new challenges. Firstly, today’s social networks do not provide sufficient tools for enhancing communication. Celebrities simply cannot filter their audience or maintain direct contact with each individual due to the limitations of direct messages.

In summary, this monetization model in web2 applications works directly through a centralized application that imposes substantial commissions, restricts content creators, and lacks the full suite of tools to maintain the audience’s trust in the influencer.

The Emergence of Celebrity Tokenization Concept

Surprisingly, the concept of personality tokenization emerged as early as 1990 when the British musician David Bowie released “Bowie bonds”, which were tied to his creative work. Investors who purchased these bonds received dividends from the sales of his albums and concert tickets. In one year, he raised just over $55 million. Bowie’s second product was “BowieNet”, which provided access to an exclusive community of Bowie’s fans, enabling direct communication between fans and the artist.

Another significant event was when BitClout first decided to create tokens for famous celebrities. Although they did not seek permission from the stars, and the tokens had no utility, users of the platform invested over $270 million in seven months, after which the project ceased to exist due to numerous lawsuits from celebrities.

These two cases confirmed a new concept of monetizing and connecting celebrities with their fans. In general, this concept includes several factors:

1. Tokenization of influencers: In contrast to the web2 concept where there is a direct connection between a centralized platform with its interests, rules, and bloggers, tokenization allows influencers to add their own tokens, enabling them to earn from their token’s value. They can also introduce utility and additional products.
2. Utilization of new platforms with audience filtering and engagement maintenance tools.

• Audience Filtering: In the world of influencers, fans can be divided into several tiers. For example, the first tier consists of the most devoted fans who follow every activity of the celebrity, attend events, and purchase the star’s products. The fourth tier includes people who are not hardcore fans but have some knowledge of the celebrity, such as those who follow them on Instagram. To ensure that influencers do not waste their time on engaging with every tier, they must know which tier each fan belongs to. To create such filtering, platforms can use strategies like paid entry into a private community, token purchases on a launchpad, or buying entry into a private community through the celebrity’s personalized tokens.

This way, influencers can allocate their resources effectively for building and maintaining audience trust and interest.

Utilization of platforms with launchpads and marketplaces:

• Launchpad: Influencers can launch their tokens that their audience may potentially buy. This marks the first step toward transitioning to a different monetization concept.
• Marketplace: This can help influencers integrate utility into their tokens and open new sub-categories for their concepts. For example, people can purchase goods from the celebrity, including access to chats, private meetings, merchandise, and more.

Notable examples of platforms with marketplaces include Cameo and OnlyFans. Cameo’s founders were the first to create a market for video greetings from celebrities. While their platform does not feature tier-1 stars, it did not prevent them from becoming unicorns with an estimated valuation of $2.5 billion. OnlyFans offers a platform for creators to provide access to private content, which can include both adult content and exclusive workouts. With just one global superstar, OnlyFans achieved an estimated valuation of $4.5 billion last year. Only the top 10 accounts on OnlyFans earned $890 million in the past year.

Even with such impressive figures, these projects do not offer full tokenization to celebrities; they lack launchpads on their platforms, and they have different development directions. However, creators and influencers can earn based on a product, not necessarily their own brand, which automatically leads to tokenization.

Currently, there are numerous projects in web3 that contribute to the development of this field. To understand their common problems, it’s essential to conduct a cluster and competitive analysis of these projects.

Competitive Analysis

The competitive analysis is based on a specific sample of projects in the field, each with its unique features, goals, and target audiences. We’ve chosen 22 projects, each with varying functions and focuses.

1. Chiliz — A blockchain-based platform that allows fans to buy, trade, and use fan tokens for participating in the governance of their favorite sports teams.
2. Social Stack — A platform that enables users to create and manage their social tokens, rewarding users for their engagement and granting access to exclusive content or experiences.
3. fyooz — A social token platform allowing creators to issue their own tokens to reward fan engagement and offer exclusive content or experiences.
4. calaxy — A platform that enables fans to buy, trade, and use fan tokens to participate in the governance of their favorite artists and musicians.
5. BlockSport — A blockchain-based platform for sports betting and rewards.
6. Try Roll — A platform for playing games, issuing tokens, and earning rewards in the form of fan tokens.
7. Fanadise — A platform for fans to buy, trade, and use fan tokens for governance of sports teams and athletes.
8. Coinvise — A platform allowing users to buy, sell, and trade cryptocurrencies and fan tokens.
9. BlockAsset — A platform providing data and analytics on the social token market.
10. Fansi — A platform for fans to buy, trade, and use fan tokens for governance of sports teams and athletes.
11. NFT Stars — A platform enabling users to create, buy, and sell NFTs of their favorite athletes and celebrities.
12. Koiime — A platform allowing users to buy, trade, and use fan tokens for governance of anime and manga projects.
13. Recur — A platform for users to buy, trade, and use NFTs of sports highlights and moments.
14. Tokenized — A platform enabling users to issue, manage, and trade digital assets.
15. Clapback — A platform for users to create and share NFTs of their own clapbacks.
16. Stageverse — A platform allowing users to create and attend virtual events using NFTs.
17. Fanverse — A platform for users to create and manage their fan communities.
18. Cameo — A platform for users to book personalized video messages from celebrities.
19. Wow Talkies — A platform allowing users to watch and create short-form videos using NFTs.
20. Knaq — A platform allowing users to buy, trade, and use NFTs of their favorite sports teams and athletes.
21. Stargazer — A platform allowing users to create and manage their fan communities.
22. MostFan — A platform that allows users to buy and trade tokens of celebrities as well as special materials from them.

To facilitate analysis, we have grouped these projects based on their primary focus. However, the essential aspect to consider within this competitive analysis is how these projects are structured. Notably, only a few of them operate from the inception of the new monetization concept to its culmination. The most challenging part seems to be obtaining agreements with celebrities.

Based on the case of MostFan and their collaboration with Roberto Carlos, it’s evident that this process is not straightforward. They’ve already paid $300,000 to secure a contract with Roberto to launch his tokens on the MostFan platform and participate in the pre-sale through his social networks.

From a high-level perspective, we can identify several common steps in this process:

1. Getting the celebrity onboard.
2. Explaining the complexities of the influencer bubble.
3. Describing how their monetization model works.
4. Paying substantial sums to each celebrity.
5. Navigating various legal issues.
6. Warming up the audience, which will later require education on using these tokens and utilities.

The difficulty is that neither influencers nor their fans are yet aware of the influencer bubble’s problems and potential opportunities. This is why out of the 22 selected projects, only three can boast having all the necessary tools on their platform to guide celebrities through this entire process. Due to these complexities, other platforms choose to focus solely on developing their marketplace, launchpad, or working with celebrities without tokenization, as in the case of Cameo.

Now, let’s delve into the tokenomics of some projects that have the full set of tools for launching and supporting celebrities.

MosFan

There is nothing unusual to note from the most critical aspects of tokenomics, except for the native token economy. Platforms of this kind naturally introduce their own tokens and allocate specific utilities within their ecosystems. These projects are thus equipped to deal with inflation. The key question is what mechanics and utilities should be introduced into the project to strike a balance between supply and demand, while ensuring that these utilities create a significant deflationary effect.

At a global level, the economy within the project depends on supply and demand. It is essential to avoid sharp declines in demand, as well as sudden increases in supply, as this could lead to hyperinflation. While demand is challenging to control, supply can be more easily regulated.

The graph illustrates the change in the issuance of social tokens over two years. Although this graph could be interpreted as an upward trend in “celebrity tokenization”, it also serves as a significant indicator that there is currently a notable imbalance between supply and demand in the social token space. In other words, there exists an imbalance between utility and token issuance. Fans are not utilizing the potential utilities offered by projects that issue their own tokens and encourage influencers to transition to a new format of monetization and fan engagement.

Chiliz

Chiliz tokenomics V2 (since 2020):

20% of the Net Trading Fees of Chiliz.net Exchange collected in $CHZ will be burnt
10% of the Net Proceed of the Fan Token Offering (FTOs) from Chiliz.net platform collected in $CHZ will be burnt* + 3 months lock on collected $CHZ.
20% of the Net Proceed of NFT & Collectibles issued by $CHZ will be burnt

TryRoll

When categorizing, you can identify six areas of focus among the projects:

1. Mixed reality (XR)
2. Web3
   - Virtual environments (Metaverse)
   - NFTs (Non-Fungible Tokens)
   - Cryptocurrency
3. Revenue optimization
   - Data monetization
   - Sponsorship ROSI (Return on Sponsorship Investment)
4. Smart stadiums
5. Sports betting
6. Sustainability

In-depth Analysis of the Social Token Sphere

The Creator Economy Is Diverse & Thriving Since 2020, the creator economy has seen exponential growth.

• More than 165 million creators have joined the creator economy since 2020, with substantial growth observed across all markets.
• In the United States alone, the creator economy has seen a growth of 34 million new creators (40%). Brazil (+73 million new creators), South Korea (+11 million), and Spain (+10 million) have also become hotspots for creative content.
• Approximately one in four people (23%) identifies as creators, sharing photos, videos, creative works, and more on social media and blogs.
• Millennials constitute 42% of the creator economy, while Generation Z makes up 14%.
• 48% of creators are universally motivated by the desire for self-expression, while less than a third (26%) are motivated by financial gains.
• Influencers make up just 14% of the global creator economy.

As stated in Goldman Sachs’ 2023 report:

“The creator ecosystem is expanding for a variety of reasons, including the growth in digital media consumption and the emergence of technologies that have lowered barriers to content creation. New platforms, such as TikTok, and established platforms like Facebook and YouTube have also introduced new formats for sharing short videos.”

As the ecosystem grows, the total addressable market of the creator economy is expected to roughly double in size over the next five years, reaching $480 billion by 2027, up from $250 billion today, according to Sheridan. This growth aligns closely with estimates for the growth in global spending on digital advertising over this period. Analysts anticipate that expenditures on influencer marketing and platform payout, driven by the monetization of platforms through advertising, will be key drivers of creator economy growth.

Goldman Sachs expects 50 million creators worldwide to grow at an average annual rate of 10–20% over the next five years. Creators primarily earn income through direct branding deals to promote products as influencers, a share of ad revenues from the hosting platform, as well as through subscriptions, donations, and other forms of direct payments from followers. According to the survey, branding deals are the primary source of income for about 70% of creators.

Only around 4% of creators worldwide are considered professionals, meaning they earn over $100,000 per year.

It’s worth noting that as early as 2020, social tokens and the creator space were considered a new trend, with a multitude of articles written by publishers and magazines such as Rolling Stones, Forbes, Nasdaq, and CNBC. Even without social tokens, projects were aiming to meet their goals without fully transitioning the influencer monetization model. This can be confirmed by projects like Patreon and OnlyFans, as well as by reassessing your selection of 22 projects, of which only 3 provide all the necessary tools. So, what are the issues in this space? Why is the target audience of these projects so diverse? Why do projects try to combine two audience clusters, and so on?

The very first objection to social tokens, which you may encounter, is the simple question: what if an influencer fails to fulfill their content posting promises to the audience? Such an objection can be approached in two ways, but we must remember that the main goal of this whole space is to elevate the level of engagement with fans and to enhance the influencer monetization model to maintain income and audience trust. In this case, you can rephrase the question: what if our favorite singer stops releasing new albums, or our favorite athlete stops playing? These questions are valid because the entire space is centered around individuals, and anything can happen. However, when asking a “what if” question, we should automatically assess the likelihood of the question’s condition. In this case, the likelihood is extremely low because, essentially, we are asking, “What if someone stops engaging in an activity that generates higher income and is directly tied to the influencer’s life?” Having understood that, we can now move on to other issues.

Upon the launch of native celebrity tokens, both the platform and the celebrities’ goal is to attract and filter their fan base. However, as platforms leverage web3 technology, a second audience segment is drawn in — the crypto-native audience. This target audience is likely not fans of any particular influencer, and they are attracted to these launches by the potential for profit.

At present, the narrative surrounding the crypto industry still tends to be negative, which may be the main reason why fans often do not transition to new platforms.

Reviewing the launch of Roberto Carlos on MostFan, the marketing team wrote 17 articles over four months explaining fundamental crypto concepts to the singer’s fans. These articles covered topics such as how to download and use crypto wallets, the difference between tokens and coins, and the workings of decentralization. Currently, addressing this issue in the social token sphere is very challenging. Platforms must effectively separate crypto-native audiences, which should have no influence on token prices and popularity, and influencers must educate their audience about crypto-industry terminology, all while building trust and clarity regarding crypto.

These two factors are exceedingly difficult, if not impossible, to accomplish for one single influencer or project, as trust and clarity are dependent on the entire industry.

The Possible Problem Solution

To address this issue, more projects are emerging, such as Flamingo, Rally, Cent, p00ls, and Socios. Additionally, older projects are beginning to implement simpler models on the surface that help influencers transition to a new monetization format while simultaneously moving away from attracting a crypto-native audience. This is done gradually, not immediately transitioning to issuing their own bonds or tokens, but through direct content sales, meet-ups, materials, and educational resources. A great example we mentioned earlier is Cameo. The platform allows influencers to filter their audience, introduces a new monetization model, and maintains trust. If, at the beginning of the article, we discussed a negative aspect related to the incomplete transition, now we genuinely understand that achieving an immediate full transition due to the crypto industry’s narrative is challenging, if not impossible.

Conclusions

1. A significant difference in advertising costs between television, traditional media, and social platforms has been a key factor in the growth of the influencer and celebrity sphere. However, the imbalance in any field gets filled, leading to a significant increase in advertising costs for celebrities and a decrease in trust in them.
2. The influencer bubble has created a problematic monetization model for celebrities, making them dependent on platforms like Instagram, YouTube, and TikTok.
3. Due to the need for better connection between influencers and their target audience, influencers are forced to filter their audience by tiers. However, modern and well-known platforms do not provide the means to do this.
4. Web3 platforms that allow celebrities to transition to a different monetization format while preserving their income and audience trust are reluctant to include all the necessary tools due to legal complications and direct contracts with celebrities.
5. Audience transition to new web3 platforms is incredibly challenging due to the mix of the crypto industry audience and genuine fans, as well as the overall narrative surrounding the crypto industry.
6. While the creator market is evolving rapidly, the social token market requires more time to shift the narrative towards it.
7. As social tokens continue to grow, all three types of social tokens are likely to succeed. Individuals or early users of social tokens will likely reap significant benefits, while issuance and platform aggregation will add considerable extra value.

Sourses

• https://www.producthunt.com/stories/a-beginner-s-guide-to-social-tokens
• https://www.nfttech.com/newsroom/an-overview-of-social-tokens
• https://www.generalist.com/briefing/social-tokens
• https://trends.vc/trends-0062-social-tokens/
• https://gov.indexcoop.com/t/iip-120-dg-launch-forefront-social-token-index-social/4076
• https://longhashvc.medium.com/social-token-economics-cdf1010c1b56
• https://www.thetilt.com/crypto/social-tokens-lessons-learned
• https://influencermarketinghub.com/creator-economy-stats/
• https://www.rollingstone.com/culture-council/articles/social-tokens-from-tokenized-things-tokenized-people-1339070/
• https://www.businessinsider.com/creator-economy-250-billion-industry-short-video-goldman-sachs-report-2023-4
• https://www.insiderintelligence.com/chart/257953/us-influencer-marketing-spending-2019-2024-billions-change
• https://izea.com/resources/insights/2023-influencer-aspirations/

Links

Website — https://y2.finance/
Twitter —https://x.com/ytwofund