CoinDesk Report:
Author: Mason Nystrom
Source:
@masonnyst
The internet is an attention marketplace where competition for attention is exponentially growing. Cryptocurrencies represent a new chapter in the attention economy story, offering mechanisms to assess attention more effectively through owned attention assets in content, social graphs, memes, algorithms, and platform social activities.
Cryptocurrencies not only change how attention is assessed but also aim to redefine the sources of attention value. In 2016, Wu Xiuming introduced the term “attention merchant” to describe how publishers and later platforms profit from user attention. Cryptocurrencies create a path for users to become their own attention merchants, reclaiming the value of their attention through ownership of attention assets.
A prominent example of this trend is seen in SocialFi, where users can own flows of attention assets such as memecoins, influencer access keys, and content. By creating pathways for users to directly engage with attention-based assets, SocialFi challenges traditional power dynamics of the attention economy, transforming users from passive consumers to active participants—new attention merchants.
Leading the forefront of SocialFi
SocialFi is emerging as a definitive category within web3. Encrypted social networks like Farcaster are thriving, with over 75,000 daily active users (DAU). Telegram bots integrate group messaging and transactions, facilitating billions of dollars in trade volume. The information market is now moving towards financializing social graphs, as seen with Twitter (i.e., trend market, fantasy.top) and Farcaster (i.e., Swaye, Perl, Arrina).
While not all social platforms come with financial incentives, SocialFi represents an evolution in social interactions—from indirectly assessing social capital to evaluating assets based on social and attention metrics more effectively. As a socio-economic technology, crypto enables social apps to add financial elements (e.g., asset trading) or integrate financial primitives natively into app layers (e.g., Friendtech SocialFi trends driven by consumer desire to own and trade attention assets. Users choose to spend time on apps that allow them to earn money based on attention or play financial games to enhance social entertainment experiences.
For instance, Fantasy, a fantasy sports trading card game and information market based on X (formerly Twitter) social graph. Fantasy allows creators to monetize their social media influence while rewarding players based on their intuition and understanding of specific social accounts. Additionally, new social networks like Friendtech, Unlonley, and Sanko enable creators to monetize social interactions directly through chat access passes. This benefits early adopters who purchase access passes, rewarding them for focusing attention on undervalued creators and groups.
At the heart of new information markets and social networks, creators and users are now attention merchants, owning attention assets within these apps and monetizing attention through app usage.
Many apps are responding to user desires to embed business and finance into social experiences:
Messaging → In-message transactions
Games → Ownable assets and in-game economies based on real money
Social → Ownable social graphs, channels, content, and platforms
Memes → Scene coins and derivative meme assets
Information markets → New markets for social entertainment, influencers, and social capital
Exchanges → Issuance of new protocols based on social and attention assets
Over the past year, the SocialFi ecosystem has rapidly expanded with attention asset exchanges (e.g., memecoin protocols), PvP (player vs. player) social games, new forms of information markets, and financialized social networks. The driving force behind this expansion lies in the maturity of crypto infrastructure in scalability and accessibility. It supports new consumer experiences (e.g., mobile PWAs), cheaper transactions (e.g., L2s), and faster app iteration cycles through improved developer tools (e.g., account abstractions and wallet-as-a-service tools).
Social Networks
Social networks roughly fall into two subcategories, each with its own creator monetization models:
Quasi-social and bidirectional.
Quasi-social networks are platforms with one-way relationships between creators and fans. One-way relationships often combine with direct profit models like subscriptions (e.g., Substack, OnlyFans, Patreon) or direct ad revenue collection from creators (e.g., YouTube, TikTok).
On the other hand, bidirectional networks are those where creators and fans have reciprocal relationships (e.g., Twitter, Reddit, Facebook, Snapchat). Bidirectional social networks allow users to profit through distribution, encouraging rather than restricting influence, similar to token-gated access (e.g., influencer-gated chats). Historically, bidirectional networks like Twitter and LinkedIn in Web2 made it more challenging for creators to profit directly from influence. Instead, creators had to resort to affiliate programs, directing users to other profitable sites (e.g., Twitter → Substack), or promotional strategies.
SocialFi reimagines users as new attention merchants, offering various new profit options for both types of social networks. Quasi-social networks enable creators to monetize audiences further by tokenizing content, influencer access, ephemeral benefits (e.g., limited-time rewards), or social status, further monetizing the top 1/3 of audiences. Quasi-social networks Drakula and Friendtech respectively tokenize content and creator roles, allowing top creators to earn income from transaction volumes. Sofamon showcases an example of a token model where individuals gradually purchase a visually appealing item (e.g., avatar clothing) until they own a wearable whole item.
Web3 social networks provide new monetization options. One example is monetizing usernames and namespace, potentially reaching millions of users with valuable namespace scales. Conversely, bidirectional social networks can better utilize in-app transactions. This could manifest as in-network markets, channel storefronts, or in-app games.
The primary difference between web3 bidirectional networks and Web2 social networks is that new attention merchants (users and creators) will be able to derive more earnings from their activities. For example, imagine if Reddit subreddit moderators could have their channels and earn income from ads they display or from transactions through their channels.
PvP Social Games
As consumer infrastructure matures, it opens up a new realm of PvP (player vs. player) social games. Particularly noteworthy are Survivor-like competitions such as Crypto The Game, Blessed Burgers, offering users new digital-native and highly social gaming experiences to win valuable prize pools. Other apps like Carpet Fun or PvPWorld offer game theory strategy games where users can collaborate to win rewards. In stark contrast to Web2, where most mobile games monetize attention through traditional ads or offer pay-to-play options (e.g., users don’t have to wait for cooldowns), game developers now have new business models, social game-like content, releasing multiple transient apps, shortening game cycles where users can gain substantial rewards before entering the next game.
New social games should optimize for: multi-winner to increase engagement; playability to make ordinary users feel highly likely to win; social interactions to further enhance the viral spread of these games. These proposed game dynamics are more incentivizing than web3 games, which historically tend towards pay-to-win or farm-first games rather than fun-first games.
New Markets and Exchanges
The dominant use case for cryptocurrencies revolves around market creation, particularly issuing new asset classes, chaining existing assets, or expanding access to digital-native assets.
Information markets
– Information markets like Polymarket could create more efficient political markets and support the creation of new event markets based on real-world events, culture, and business.
Attention Exchange
– Platforms like Pump and Ape Store enable users to create new assets (e.g., memecoins) based on quality: attention. Additionally, Sofaman digitizes brands by allowing users to create Telegram-based avatars, selling branded clothing on a curve union.
Telegram Bots
– Telegram bots bring markets and social finance games into the messaging experience, providing users with a more convenient experience.
Points and Pre-tokens
– Points have always been an effective incentive strategy for teams to test user behavior and try dynamic incentives. Points markets (such as Michi and WhalesMarket) and pre-token markets (such as Aevo) can help create more efficient token markets.
Several sub-trends are driving the creation of new markets and exchanges. First, the rise of verticalized social and financial platforms is pushing these apps to issue new types of assets. Secondly, by earning points, tips, and tokens, users continuously increase ownership of on-chain activities, expanding the asset surface area with which users can interact, encouraging the creation of new trading venues. Finally, users are now interacting with assets like memecoins, feeling a greater sense of autonomy. Similar to cultural assets in the real world (e.g., sneakers or music), users have a sense of control over the popularity and potential appreciation of these cultural assets because the fundamental metrics that give assets value (user attention) are controlled by end consumers.
Creating New Attention Merchants
The social landscape is undergoing a paradigm shift where dynamic relationships between users, creators, and attention are being redefined. At the core of these trends is the shift of users and creators from the supply and demand of the attention economy to becoming merchants of their own attention.
Designing new financial or social elements is undeniably challenging, let alone integrating the best of both into a unified experiential element. The early social finance tools, toys, and games of the next era of SocialFi networks and apps will be those that rapidly run experiments, test new consumer behaviors, and capitalize on emergent behaviors to reveal consumer preferences.
