---
title: 'Tweet for tweet: Top 30 cities on Twitter'
date: '2008-04-09T20:08:48-07:00'
type: post
word_count: 388
char_count: 2538
tokens: 505
categories:
  - board
  - leader
  - MattKing
  - Oregon
  - Portland
  - Portland_OR
  - Twitter
  - TwitterLocal
tags:
  - board
  - leader
  - Oregon
  - Portland
  - Tweet
  - Twitter
  - TwitterLocal
---

# Tweet for tweet: Top 30 cities on Twitter

Portland-based [TwitterLocal](http://twitterlocal.net "TwitterLocal"), the service built by [Matt King](http://mattking.org "Matt King") that allows you to create an RSS feed of [Twitter](http://twitter.com "Twitter") users for a particular location, has just moved added a feature that takes the site from a one-time visit to a regular destination—[a leader board for the top 30 cities on Twitter](http://www.twitterlocal.net/stats "Top 30 cities on Twitter").

The leader board currently ranks cities by the number of tweets by residents in a rolling 24-hour period.

Glancing at it a few minutes ago, Tokyo was in the lead with San Francisco running a close second. Paris leads the Europeans. And our hometown of Portland is sitting around #14 or so.

From 8:00PM, April 8, 2008 through 8:00PM, April 9, 2008, the list looked something like this:

1. Tokyo
2. San Francisco
3. New York City
4. 寅島市南区
5. Paris
6. (*Japan*)
7. (*Entre mi cuarto y mis zapatos*)
8. London
9. São Paulo
10. Los Angeles
11. Chicago
12. Seattle
13. Toronto
14. **Portland, OR**
15. Boston
16. Washington, DC
17. (*United States*)
18. Austin
19. (*Mexico Distrito Federal*)
20. (*California*)
21. Atlanta
22. Taipei
23. Sydney
24. London
25. Osaka
26. (*Brazil*)
27. Madrid
28. (*Mexico*)
29. Melbourne
30. Barcelona

As you can see, there is some weirdness can show up in the results. King notes these flaws in the system:

> - The seemingly high count of random places like “my pc”, “cybertron”, etc. are the geocoding service’s way of having fun. It seems some fake locations get assigned coordinates to somewhere in Kansas.
> - There is also a very high count of locations with asian characters, which again the geocoding services give only one location. Other than that the numbers are fairly accurate.

Despite these minor foibles, TwitterLocal’s leader board is the first location-specific Twitter analysis that I’ve encountered which actually begins to show which locations have caught the Twitter bug.

And as impressed as I was with TwitterLocal’s service, I’m sure to find this type of competitive ranking completely addictive, at the very least. I’m sure I’ll be checking [TwitterLocal leader board](http://www.twitterlocal.net/stats "TwitterLocal leader board"), obsessively, over the coming months to see if we can get Portland to crack the top 10. At the very least.

Did your hometown make the list? [There’s only one way to find out](http://www.twitterlocal.net/stats "TwitterLocal leader board").