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Yup that's definitely true, population centers rank highest for most topic lists (especially New York where meetup.com was founded) The original use-case I env

Yup that's definitely true, population centers rank highest for most topic lists (especially New York where meetup.com was founded) The original use-case I envisioned for something like this is someone deciding which cities they might like to move to by choosing cities that have a lot of people with shared interests. So should the metric for that be total people that are part of a topic, or the % of total city population engaged in that topic? I've currently chosen the former, but interested in what others might think. Thanks for the feedback, -pH+

theli0nheart 10y ago
I agree with erex78. The former measurement doesn't tell me much; I already know what cities have the most people. The latter measurement better indicates the probability of a chance encounter with someone who has your shared interests.
- ponderingHplus 10y ago
  Yeah that's a good point. I like scribu's point that it can be somewhere in between. I'll have to think on that a little.
  - baccheion 10y ago
    Usually (taken from erf/error based on sample size), something grows proportional to the square root of the sample size. If using raw sample sizes, you can apply a square root to that sample size before using it (meters its impact).
  - deleted 10y ago
    [deleted]
scribu 10y ago
> So should the metric for that be total people that are part of a topic, or the % of total city population engaged in that topic? Ideally, both. You want to have a community with at least N people, but cities with a high % should rank higher. Could also account for the number of total meetup.com members in that place.
- ponderingHplus 10y ago
  Hmm interesting, I'll give that some thought. Thanks!
erex78 10y ago
You could have a toggle where you divide by the overall population of each city. So basically let the user switch between percentage and absolute. Another ranking to consider is the h-index metric for academic papers (https://en.wikipedia.org/wiki/H-index https://en.wikipedia.org/wiki/H-index), where you use the number of members of each meetup group in place of citations. So a city with a score h has h meetups each of which has at least h members.

theli0nheart 10y ago

I agree with erex78. The former measurement doesn't tell me much; I already know what cities have the most people. The latter measurement better indicates the probability of a chance encounter with someone who has your shared interests.

ponderingHplus 10y ago
Yeah that's a good point. I like scribu's point that it can be somewhere in between. I'll have to think on that a little.
- baccheion 10y ago
  Usually (taken from erf/error based on sample size), something grows proportional to the square root of the sample size. If using raw sample sizes, you can apply a square root to that sample size before using it (meters its impact).
- deleted 10y ago
  [deleted]

scribu 10y ago

> So should the metric for that be total people that are part of a topic, or the % of total city population engaged in that topic? Ideally, both. You want to have a community with at least N people, but cities with a high % should rank higher. Could also account for the number of total meetup.com members in that place.

ponderingHplus 10y ago
Hmm interesting, I'll give that some thought. Thanks!

erex78 10y ago

You could have a toggle where you divide by the overall population of each city. So basically let the user switch between percentage and absolute. Another ranking to consider is the h-index metric for academic papers (https://en.wikipedia.org/wiki/H-index https://en.wikipedia.org/wiki/H-index), where you use the number of members of each meetup group in place of citations. So a city with a score h has h meetups each of which has at least h members.