Acquisition and visualization of tweets.
For an hour during the evening of the FBI raid of Michael Cohen’s office, I streamed some tweets. I collected any tweets including the word Trump, guns, nda, Cohen, Stormy, or FBI.
More or less, this is what people were talking about
The most commonly used words.
And the most common hashtags
Word network of words used together at least 100 times
And to thin out the network a little, word network of words used together at least 200 times
To see what the tweets were actually about, I ran a topic model, using LDA. The words in the legend are those that best represent the topics. LDA is probabilistic, and I have included only tweets that have a greater than 80 % chance of being in the assigned topic. Move your mouse over each point to see the tweet it represents.
See the plot here
It’s interesting to see the topics, but it’s more interesting to see the coocuring word networks for each topic.
offices, daniels, michael, man
ed, like, news, michael
doj, hilary, clinton, loudobbs
tell, let, right, act, ag
president, potus, make, sessions
So that’s what twitter looked like, more or less, during the evening after Michael Cohen’s office was raided by the FBI