https://6sigma.com/twitter-as-combinatorics/ Six Sigma Certification and Training Fri, 28 Feb 2025 06:39:28 +0000 hourly 1 https://6sigma.com/twitter-as-combinatorics/#comment-25049 Mon, 05 Jan 2009 14:20:25 +0000 https://opexlearning.com/resources/?p=845#comment-25049 Great Henri Poincaré’s beard, you have made my day! I see you have more like this; amazing. Looking forward to plunging into the archives.

]]> https://6sigma.com/twitter-as-combinatorics/#comment-25048 Mon, 29 Dec 2008 14:02:29 +0000 https://opexlearning.com/resources/?p=845#comment-25048 Your equations seem solid enough. What may be interesting is to figure out the ranking of someone’s ‘assymetric following’, which could be an indicator of their popularity.
1. If we assumed that the baseline model would be that everyone in a group connects to everyone else in that group, then we would have the n(n-1)/2 model. Let’s call this number B (for Baseline).
2. However, if someone has a huge following, then their number of connections would deviate from that baseline. As you state: [n r] [n!/r!(n-r)!]
3. Because r would be lower, r!(n-r)! would be smaller; the overall equation would be higher number. Let’s call this number C (for Cool factor).
4. The difference between B and C would be the degree to which someone has an assymetric following. It may be a way to rank their cult-like personality.

]]> https://6sigma.com/twitter-as-combinatorics/#comment-25050 Mon, 29 Dec 2008 09:55:05 +0000 https://opexlearning.com/resources/?p=845#comment-25050 RT: twitter with a scientific, mathematical twist: http://tinyurl.com/9hu8vy by @shmula Nice, geeky read.

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