neural networks

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trixydoza

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Friends reunion: Comic artist develops robot to generate new Friends episodes

There are some obvious porkies in the above story, probably for the sake of entertainment, but a similar analysis of four-year text for AFF using Word2Vec and a couple of proprietary extensions reveals some obvious things, which makes the less obvious ones all the more interesting:

blackcat20 and TomVexille really like each other
Dr Ralph and BettyB like each other even more
Threads have greatest probability of going to **** (defined in algorithmic terms) with participation by JohnK where he uses the word "sorry" within his first three contributions
Threads are longest with participation by JohnK
The shorter the average contribution to a thread, the greater the average number of likes
Threads with higher frequencies of numbers tend to have more use of the word "hat".
Among major countries, the one with the highest correlation to smily-type emoticons was Japan.
 
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Oh goody. I get 2 references in this thread. You must really like me a lot.

Sorry....
 
Does Word2Vec give any insights into which other AFF member's posting style (word usage, phrasing, etc) is most similar to yours?
 
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