I used twitter4j and R to make a word map of Donald Trump’s tweets. I thought it would be interesting to see what his most used words are. The program downloads 3000 of his most resent tweets, unfortunately it cannot download all of the extended mode tweets. Only the first 140 characters. It wasn’t that interesting in the end.
I have processed more of the Daniel Morgan data, and thus have an updated network of the data. Below is a visualisation of the data produced by extracting the network structure from Neo4J using R and iGraph, then saving the network as a gexf file and importing into Gephi. The network is more complete but also has edge labels.