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Rough stats: 0: World pop: 7.7b 1: People with phones: 5b 2: People with emails: 3.8b 3: Facebook MAU: 2.5b/1.5b DAU 4: WhatsApp, Instagram: 1.5b users/1b DAU 5: Twitter: 320m MAU List index = graph intelligence quotient band (GIQ). Twitter is only *large* band-5 GIQ hive mind
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I’m just eyeballing it, but it would be useful to build a measure of GIQ to capture the computational quality of a hive mind based on topology, grammar of connection. Each If the band is int(log(GIQ)) on base 2, Twitter is 2x smarter than the messengers and 4x smarter than FB.
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There are many higher-band hive minds. I’d estimate github at say band 7 or 8. But they are not as big as these big ones with a meaningful share of world population on board. I’d put the cut-off for true hive minds at 1% of world pop, or about 150m active users.
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Analogy between brains and social graphs is probably better than you think. The big diff is that our synapses have a smaller signaling vocabulary. Brains use 0/1 signaling to 1st order. Human graph intelligences during emotional-phatic-speech are also 0/1 (sad/happy contagion)
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As our signaling at h2h level increases in sophistication, it doesn’t travel as far. A propositional logic statement (0/1) with an attached sentiment (positive/negative) can travel much farther than your nuanced tweet with 3 layers of irony. So most GIQ is tiny-instruction-set.
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The message complexity median message in a medium that propagates beyond say a local Dunbar-scale neighborhood (~150), aka “goes viral” is probably a good indicator of the computational sophistication of the graph intelligence. On Twitter that’s obviously a meme or epigram.
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Interestingly enough, any subcultural @ conversations here that seem valuable to you are by definition irrelevant since they don't propagate. They are attachment glue. What you value on Twitter is almost certainly functionally a benign mind-parasite that doesn’t help hive mind
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This is a follow-on to my thread yesterday.
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A megatrend hypothesis inspired by several microtrend that I think are related: a) waldenponding b) rise of heavy duty information management methods like @fortelabs BASB (build a second brain) c) conversational media eating authorial media d) "hivebrain" jokes/references
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Heh large-scale patterns of blocking/muting/ghosting are like repression patterns requiring psychoanalysis. I bet I’d make a good graph-mind Freudian therapist the way Susan Calvin in Asimov robot books was a robopsychologist.
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