{"id":5496,"date":"2010-12-20T19:25:48","date_gmt":"2010-12-20T11:25:48","guid":{"rendered":"http:\/\/www.intmath.com\/blog\/?p=5496"},"modified":"2013-07-30T17:19:29","modified_gmt":"2013-07-30T09:19:29","slug":"twitter-follower-semi-log-graphs","status":"publish","type":"post","link":"https:\/\/www.intmath.com\/blog\/mathematics\/twitter-follower-semi-log-graphs-5496","title":{"rendered":"Twitter follower semi-log graphs"},"content":{"rendered":"

Here are some interesting distributions, and another \"real-life\" application of semi-log graphs. <\/p>\n

The information comes from Hubspot's State of the Twittersphere report<\/i>, dated Jan 2010, which is unfortunately no longer available.<\/p>\n

One of their conclusions:<\/p>\n

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The vast majority of Twitter users have networks under 100 people, [with] 82% of Twitter users having less than 100 followers, and 81% of Twitter users are following less than 100 people. <\/p>\n<\/blockquote>\n

This makes sense to me. If you follow thousands of people, how can you hope to read and respond to even half of them?<\/p>\n

This reminds me of Dunbar's Number<\/a>, the idea that humans tend to cluster in groups of around 150, since that is the limit of reasonably expecting to know everyone in the group.<\/p>\n

But the low number of following\/followers is more likely explained by the large number of people who would start Tweeting, then give up.<\/p>\n

Twitter - most followers<\/h2>\n

As I write, the top 3 people on Twitter with the most followers (according to Twitaholic<\/a>) are:<\/p>\n\n\n\n\n\n
 <\/td>\nFollowers<\/th>\nFollowing<\/th>\n<\/tr>\n
Lady Gaga (ladygaga<\/a>) <\/td>\n7,394,362 <\/td>\n145,898<\/td>\n<\/tr>\n
Britney Spears (britneyspears<\/a>)<\/td>\n6,416,696<\/td>\n416,140<\/td>\n<\/tr>\n
Justin Bieber (justinbieber<\/a>)<\/td>\n6,355,747 <\/td>\n95,167<\/td>\n<\/tr>\n<\/table>\n

Barack Obama is #5 on this list, with over 6 million followers.<\/p>\n

Twitter - follower distribution<\/h2>\n

Now to the graphs. They have used a semi-log scale<\/b> for these graphs so we can see more detail at the higher end (a million plus) and for the more \"normal\" number of followers.<\/p>\n

\"twitter-distribution-followers\"<\/p>\n

This graph reminded me of Zipf Distributions<\/a>, another place we find semi-log graphs.<\/p>\n

Twitter - following distribution<\/h2>\n

And for the distribution of the number of people Twitterers are following:<\/p>\n

\"twitter-distribution-following\"<\/p>\n

There is a \"blip\" in the middle of that last graph. It is explained by the fact that Twitter imposes a temporary limit on following at the 2,000 level.<\/p>\n

Twitter - patterns of use<\/h2>\n

Other findings from Hubspot's report were interesting:<\/p>\n

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