Love vs. Fame

Summary

Li Jin makes the argument that there are two types of social network products: love and fame. Love products, such as Whatsapp, iMessage, and Facebook allow you to talk to your existing connections, maintaining those connections. Fame products are those where you find new connections/discover new people.

The business model of love products is subscriptions. Eg. Discord or Twitch.

Is Disord a love product? I think of Content Guild, Optimism, etc. I should feel like I know these people. Hmm the distinction btwn love & fame seems to not be as black/white as Li Jin makes it. Bc I use “fame” products such as Twitter for love as well. I actually know people. Hmm I know the influencers. Normies don’t know influencers personally.

(my two cents: I’ve heard that fame platforms like Twitter enable you to feel closer than ever to people who you admire/follow, but you don’t actually know them. Like schoals research or the goodreads person, though the TG stream I actually feel close to him. I’m his fan.)

Notes

Love social media products enable people to connect more intentionally with another and are often marked by bidirectional relationships

Fame social media products are one directional relationships otherwise known as “followers”

The business model of fame products is to keep users engaged for as long as possible by continuing to show them new content

The dichotomy between love and fame products is what differentiates social networks from social media

Crypto enables the creation of new types of networks “socioeconomic” networks which are ownership networks (versus purely social network)

Quotes

On the love side of the spectrum are products that focus on deepening connections with others. Examples are iMessage, WhatsApp, early Facebook, and Discord. The value proposition is connecting more intentionally with others, cultivating existing relationships, and intensifying affinity. These products are often marked by bidirectional relationships, like friendships on Facebook or iMessage. When users use a product like Discord or WhatsApp, they usually do so for a particular community or person—not to discover new content. These products reinforce this value proposition by featuring a deterministic algorithm (if person A sends something to person B, the other person will always receive it).

Fame products are where you can discover new people. Twitter has become more of a fame product.

On the fame side of the spectrum are products that help users get exactly that: fame or reach. These products are built around discovery of new content and creators. Examples of fame-centered social products include YouTube, Instagram, TikTok, and Twitch. ==These products feature one-directional relationships (or “followers”). Influential users professionalize, becoming creators and reaching ever-larger audiences—a dynamic that’s not present on bidirectional social networks==. Products on this side of the spectrum feature probabilistic algorithms, where content gets shown depending on the likelihood of engagement, so users aren’t guaranteed to reach their followers.

However, fame-based products have more uncapped network effects: users can be shown content from anyone, and utility continues to improve as more users join. Under the dominant business model of advertising, keeping more users engaged for more time is the north star goal, and the fame-driven model is more advantageous for scaling users’ attention—and revenue.

==The dichotomy between these two ends of the spectrum could be summed up as social networking vs. social media.

==I often hear people say they feel that, on a broader level, social networking is moving toward social media; apps that once focused on friends now focus on entertainment, and everyone is expected to be a creator now. Instagram, once used for keeping up with friends’ lives, is now used in large part to follow creators and brands.

A mix of both types creates retention.

• Does volume matter for love products? Probs not?

==Social networks featuring bidirectional social graphs hit a ceiling of network effects once users reach the limit of who they know.

==Zooming out, the biggest outcomes in social have historically arisen from the creation of new networks: from IRL friend-based networks (Facebook) to interest-based (Reddit, TikTok) to knowledge-based ones (Quora). There’s an opportunity for crypto to take a crack at building a new type of ownership-based network that leverages onchain assets as the basis for new communities. We refer to this idea as a socioeconomic network (versus a purely social network).

==I believe new business models will emerge to support different and smaller networks than what can viably exist under ad-based models, fulfilling humans’ need for social status and connection in novel ways.