Test it for yourself here.
What are Markov Chains?
Markov Chains are a way of modelling states of something and using probability to determine a likely next state. For example if you are sitting, your next state might be as follows... 50% continue sitting, 30% standing, 10% lying down, 10% running.
As per usual someone else already has an amazing explanation with animations. So if you want to learn more check that out here.
How do we use this to generate text?
So first we need to have a data set. Any text will do, and the bigger it is the better. In this example I use Donald Trump's last ~30,000 tweets.
You could try this with any other data set, maybe the bible, news headlines, some shakespeare or a favourite poet.
Next we go through the text and for each word we have we create a list of words that came after it. This is an example of the word Fake.
{
"word" : "Fake",
"followedBy" :
["News","News","News","News","Whistleblower?","Impeachment!","News","Whistleblower?","News","News","News","News","Hearing","Whistleblowers","Washington","News","News","News","News","News","News!","News","Washington","as","News!","News!","News","News","News","News.","News","News","News","News","News","News","News","News!","News!","News.","News","News","Whistleblower","News","News","News","News!","News","News","Witch","News","News","News","News","News","News","News","News","News!","News","News!","(Corrupt)","and","News!","News","News","News","News","News","and","Poll","News","News","News","News!","News","News","News","News","News","News!","News","News","News","News","News","News","they","News","or","News!","Interview","story","News!","News","News","News","News","and","News","News","News","News","News","News","News","and","and","News","News","News","News","News","News.","News","News","News","News.","Media!","News","News","News","reporting!","News","News","News.","News","News","News","News","News","News!","News","News","News.","News","News","News.","News","News","News","Polls.","News","News","News","News","News","News","News","News","News","unsourced","News","News","News","News","News","and","News","News)","News","News","News","News","Polls","News","News","News","News","News","(Corrupt)","numbers","News","Polling","(Corrupt)","numbers","News","Polling","News","News","News!","and","News","News","News","News!","News","News","News","News","News","News.","News","Stories","work","News","News","News!","Media","News","News","News","and","News","News","News","News","News","News","Dossier)","News","News","News","News","and","News)","News","News.","News","News","News","News","News!","Dossier’s","Story","Story","News","News)","News!","News","News","News","News","News","News","News","News","News","News","Dossier","News","Dossier","News","News.","Dossier","News","News","Science.","News","News!","News!","News","Dossier","News","News","Dossier","Media","News","News","News!","Fact","News","News.”","News","News","News","Media","and","News","News","News","News","News!","News","News","News","News","just","News","reporting","reporter","News","News","News","News","News","News","News","sources","News","News","News","News","News","News","News","News","News","News","News","News","News.","News","News","News","News.","News","News","News","60","Media","News","News","News","News","News.","News.","Suppression","News","News","News","News.","News","News","News","News","Story","News!","News.","News","News.","Dossier","News","News","News","News","NBC","Dossier","nothing","News.","Reporting","News!","Reporting","News!","News","Dossier)","News","News","CNN","News","CNN","New","CNN","News","News","News","News","News","Story","News","reporters","News","piece","News","as","Dossier.","News!","News","Dossier","News","News","Dossier","News","News","News","News","News","News","News","News","News","News","News","News","Dirty","News","News","News","News","News","News","News","News","News","News","News","News","News......","News","News","News","News","News","Media","News","ABC","News","News","News","News","News","News","News","News!","News","News","News","News!","News","News","News","News","News","she","News","News","News","News","News","Mainstream","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","Russia","News","News","News","News","NBC","Washington","News.","News","News","Memos?","Dossier","News","News","News","News.","News","News","News","News!","News","News","News","News","reporting","News","News","News","Book","News","News","News","Book","News","News","News","News","News","News","News","News","News","Polls","News.","News","Mainstream","News","News","News","News","News.","News","News","News","News","News","News!","News","News","News.","News","News","News","News","News","News","Dossier","News).","News","News","News","News","News","Dossier","Media","News","News","News","News","@NBCNews","News","News","News","News","News","News","most","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News","News.","News!","News","News","News","News","Media","News","News","News","News","News","News","News","News","News!","News","News","News","News","News","News","News.","News","News","News","Media","News.","News","Media","News","News","News","Media","News","News","Trump/Russia","News","News","media","news!","News","Tears","News?","Twitter"]
}
So when we come to generate some new text we can start with a word, then randomly choose a word to come after it from the list, then repeat until we have a sentence (I like to finish on a full stop).
So in the above example the most likely word to follow "Fake" is "News". Who would have guessed.
How accurate is it?
Not great. This solution doesn't consider Natural Language and this means the results can just be gibberish.
However in saying that a lot of the results are quite amusing.
Source code available here.