In this post i want to focus on the stats I gathered about the distribution of twitter updates. The data simply represents % of the posts made with each service. Twitter-addicts usually use clients and update more frequently so if we would want to track unique users instead of posts ammounts I expect the weight of web-updates would rise dramatically. I'll digg more inside the stats as i move on with my project.
Please note, that "TwitterFeed" actually updates Twitter automatically without user interaction. So as i move on in this post, I'll break data into smaller sections.
update method | popularity | web | 46,83% | im | 5,83% | txt | 5,17% | twitterfeed | 6,67% | twit | 6,50% | twhirl | 6,33% | twiterrific | 5,17% | P3:PeraPeraPrv | 2,33% | twitterfox | 1,83% | twinkle | 1,67% | movattwitter | 1,50% | other | 10,17% |
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Let's see how it looks like if we compare the services that twitter owns vs. 3d party clients. RSS updates are excluded from the calculation.update method | Twitter + TXT + IM | 3d party clients | popularity | 62% | 38% |
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And the most popular Twitter clients in May were:
update method | popularity | twhirl | 17,84% | twiterrific | 14,55% | twit | 18,3% | twitterfox | 5,16% | P3:PeraPeraPrv | 6,57% | movattwitter | 4,22% | twinkle | 4,69% | other | 28,63 |
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Japanise language Twitter clients got an impressive 10,33% share.
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