Hi Peter,
I tried to do something to answer your question a couple of years ago
and presented it in Velocity Sevilla. I surveyed people who were part of
a Facebook group ("Mejor en Bici" - Better by Bike) and used almost the
same survey for people who were part of a bike ride group ("Ciclopaseos
de los Mïercoles"). My methodology was pretty basic and I didn't really
do a thorough statistical analysis (plus groups were partially
overlapping), but I did "find" that people who were part of the bike
ride were using the bike more than the ones part of the Facebook group
(when compared to before taking part in the biweekly rides / facebook
group).
I am offline so can't browse for the link, but I'm happy to share some
info on it, though it's mostly in Spanish.
Best regards,
Carlos.
On 23/08/2012 10:05 p.m., Jonathan Daly wrote:
> Hi Peter
>
> Check this out. It's not cycling specific but it's some research on the tipping point threshold for social networks.
>
> http://news.discovery.com/human/opinion-minority-rules-110804.html
>
> Cheers
> Jonathan
>
>
>
> On 24/08/2012, at 6:19 AM, Peter Wood <[log in to unmask]> wrote:
>
>> Hello,
>>
>> Literature question: does anyone know of any data, or even rules of thumb regarding critical thresholds in social networks? Any qual or quant research into the matter would be interesting, I'm not expecting rigorous specific numbers.
>>
>> Obviously it will be quite a sweeping statement, or need a lot of specifying, but is there a point at which you're likely to see particular effects happening. For example, within a given community or area if:
>> 1% of commutes are done by bike then "people keen enough to cycle to work" are "other people" who you see on the road but you don't know any,
>> at 5% they're a constant presence but you still might not know anyone personally (or it's "bob the cyclist, you know, from catering"),
>> at 10% everyone has to have a friend/colleague who cycles,
>> and at say 30% they're inescapable.
>>
>> Pete
>>
>> Open Uni
>> Geography dept
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