Home > Uncategorized > Some guesses about the future of social media, part 1

Some guesses about the future of social media, part 1

Let’s fast-forward twenty years, and assume a few things:

  • We don’t melt the planet, blow ourselves up, or otherwise change the game so radically that any projections become meaningless.
  • Technologies for speech recognition, natural language processing and open-domain question answering have evolved to the point where you can just ask your computer any well-framed question and get a decent answer (or get a referral to a human being who has a good answer). Think HAL or Star Trek.
  • Social media adoption continues to grow, so that most people on Earth are engaging in some form of social networking.
  • Telepresence technologies are commoditized to the point where you can remotely interact with any group of people on Earth as if you were all in the same room.

Assuming those things, what will the mainstream social media behaviors look like in twenty years? Will it just be YouTwitFace on steroids, or something totally different?

Technology will open up an almost limitless array of possible social behaviors and interactions, and put the sum total of human knowledge at our fingertips while we’re engaging in them. But once technology is no longer a limiting factor, I suspect that those behaviors will be shaped much more by the way we’re wired as human beings than by technology itself. Here are a few “hard-wired” human attributes I think will come into play:

Dunbar’s Number

[From Wikipedia] “Dunbar’s number is a theoretical cognitive limit to the number of people with whom one can maintain stable social relationships. These are relationships in which an individual knows who each person is, and how each person relates to every other person. […] No precise value has been proposed for Dunbar’s number, but a commonly cited approximation is 150.”

This number was first proposed by British anthropologist Robin Dunbar, and is based on studies that show good correlation across primate species between neocortex size and average group size. So primates with larger brains tend to live in larger communities where everyone knows who everyone else is, and we humans top out at about 150.

Phatic communication and “exhaust data”

Another human attribute is our need for “phatic communication”. I found a brilliant and very entertaining explanation of this in Grant McCracken’s blog post “How social networks work: the puzzle of exhaust data”, but here’s a short version: humans and all social mammals spend a huge amount of time engaging in small talk, ie. communication that does not actually convey any information. The purpose of phatic communication is simply to acknowledge that we’re still plugged into the social network: I exist, you exist, the channel is open, the network is active and flowing. Twitter and LinkedIn updates are a great example: I may not care that John is now connected to Mary or what Fred ate for breakfast, but it’s comforting to be reminded that they’re still out there.

Conformity vs. Individuality

This is the basic tension between our need to belong to a group, and our need to distinguish ourselves in some way within that group. These were largely shaped by evolutionary pressure: if N’garr can’t get along with his fellow cavemen, he will get kicked out and is less likely to pass along his antisocial genes. But if he fits in, and is able to turn a natural talent into a special role that is valuable to the group, he will have many babies (and possibly a longer life to pass his knowledge on to the group).

The guest-host relationship

I wrote a bit about this before, here, as it relates to corporate digital communications. The guest-host relationship is a human universal: most cultures agree on what it takes to be a good host when you bring guests into your home. It will be interesting to see if the same rules apply, or how they evolve, once telepresence lets us invite guests into our “virtual homes”.

Next time I want to make some guesses about how these human attributes might shape the future of social media. I’ve made some wild assumptions and taken a lot of shortcuts to get this far, so I would welcome any feedback, critiques or flames before i stick my neck out even further. Mi casa es su casa 🙂

  1. Ben Edwards
    April 4, 2010 at 10:46 am


    How about anti-social behaviors? Aren’t these just as important to understand as social behaviors? I wonder whether there is an opportunity to help design away certain anti-social behaviors. For example, Amazon’s reputation algorithm is designed to surface the most “useful” book reviews and display them in order of usefulness as a default setting. If Amazon’s algorithm really does surface useful reviews, reviews that are less useful are made less visible, discouraging people from writing them. Similarly, slashdot and reddit use algorithms that suppress flaming – an ancient form of anti-social behavior where the ad hominem attack derails the conversation.

    • April 4, 2010 at 1:28 pm

      Great point Ben, thanks for your feedback. Your examples got me thinking about the different kinds of mechanisms we currently have to suppress antisocial behavior. I can think of three main ones:

      – algorithmic: eg. your example of Amazon’s collaborative filtering system, and other purely rule-based systems, eg. badword filtering or spam filtering.

      – peer-based: direct policing by the other members of the network — eg. the ‘mark as inappropriate’ function in most social networks, ranking/rating, or direct responses to flames. These can also used as input to the algorithmic systems, so the lines are a bit blurred between the two.

      – institutional: any direct intervention by the administrator of the system, eg. suppressing a contributor’s posts or locking him out of the system.

      One possible game-changer here would be a move towards sharing and standardizing antisocial behavior data across all social networks. Very similar to what’s happening in the “real” world with the sharing of financial data to establish credit score, criminal records, tax records, etc.

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