Types of Communities
- Interest-based → same interests/passions
- Location-based → same geographical location, place of work, etc.
- Vibe-based → group energy
- Circumstance-based → external influence, put into the same group
Can we ever have fully digital commons?
How large can communities get before they decay? Relevant: group limits
- get social status points
- we will choose to identify with whatever in-group will immediately benefit us the most
- why sororities + frats are successful → sunk cost fallacy
- amount of boundaries required → well organized events vs serendipitous interactions
- do serendipitous interactions only come from ephemereal content?
Turing Test for communities
heuristic from Austin Wu
A very computational view of communities but is it possible to test for value alignment within a community like a Turing Test? If the community feels and behaves like a person, then its values are aligned?
How do we quantify this if vibes are unoptimizable?
The “90–9–1” version of this rule states that for websites where users can both create and edit content, 1% of people create content, 9% edit or modify that content, and 90% view the content without contributing.
Was called “participation inequality” by researchers at AT&T labs
the 80/20 rule known as the Pareto principle states that 20 percent of a group will produce 80 percent of the activity, however the activity is defined.
a type of power law (zipf’s law)
Size of the community might matter? a form of Dunbar’s Number e.g.
- small communities like family group chats -> almost everyone creates content
- large communities like LinkedIn -> most people consume, vocal minority
though size might just be a proxy for sense of belonging in a group. i.e. if you strongly identify with said group (family) you are more likely to participate and contribute
in larger communities then, the approximately normal distribution of people who are engaged in the community may lead to some type of power law