My cousin Antony pointed me at the work of Tarde (and earlier, Leibniz) on the concept of monads
A paper by Latour (see
http://www.bruno-latour.fr/node/144
for background and google for the full paper/chapter)
so social nets as graphs can see aggregates and individuals as properties of
the set of edges and verticies - so that lets us unify this model - provided we
capture sufficiently rich types of edges (kinship relationships, types of
friendships, encounters, co-membership of clubs, geo-spatial relations,
psycological, etc etc)
it also mighr help explain the dicomty in economics/history where most the
time, most effects are caused by large group behaviour (a la marxist analysis)
but from time to time, indivuduals wirled great influence and impact outcomes
(classical) - so this is just when someone is a hub at a time when opinions are
"hypercritical" ?-- balanced between one extreme and another -- when that
person can sway a large number around them because of their centrality and
degree....
hmm... .. ..
fits with the whole peer-progressive thing too
so this is where small data (and anecdotes and narratives) meet big data
and its also why the butterfly's wingflap causing a hurricane could be something we'd eventually model properly (after all, a trillion butterfly wingflaps happen every year without hurricanes, so its a matter of modeling the right butterfly, or the right Genghis Kahn).
I'm also pointed at Sandra Gonzalez Bailon's paper on this:
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2238198
I also like Kate Crawford's very nice talk on this topic ....
http://www.youtube.com/watch?v=irP5RCdpilc
A paper by Latour (see
http://www.bruno-latour.fr/node/144
for background and google for the full paper/chapter)
so social nets as graphs can see aggregates and individuals as properties of
the set of edges and verticies - so that lets us unify this model - provided we
capture sufficiently rich types of edges (kinship relationships, types of
friendships, encounters, co-membership of clubs, geo-spatial relations,
psycological, etc etc)
it also mighr help explain the dicomty in economics/history where most the
time, most effects are caused by large group behaviour (a la marxist analysis)
but from time to time, indivuduals wirled great influence and impact outcomes
(classical) - so this is just when someone is a hub at a time when opinions are
"hypercritical" ?-- balanced between one extreme and another -- when that
person can sway a large number around them because of their centrality and
degree....
hmm... .. ..
fits with the whole peer-progressive thing too
so this is where small data (and anecdotes and narratives) meet big data
and its also why the butterfly's wingflap causing a hurricane could be something we'd eventually model properly (after all, a trillion butterfly wingflaps happen every year without hurricanes, so its a matter of modeling the right butterfly, or the right Genghis Kahn).
I'm also pointed at Sandra Gonzalez Bailon's paper on this:
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2238198
I also like Kate Crawford's very nice talk on this topic ....
http://www.youtube.com/watch?v=irP5RCdpilc
