How it has been done
Using Kimono, it's possible to gather part of the dialogue which constitutes the contest of every sentence containing the word "NSA" (1075 sentences containing this word with the relative link to the context) from the links grouped before on Subzin. These links are inserted in Kimono and the crawl is activated. The result is a datatest in which in every line there is a sentence (5375 total sentences). All those sentences are copied in the website Textalyser, which allows to have a list with the most common words with the number of times they appear in the text. Only those with a frequency major than 6 have been selected. Then these ones have been divided in one of these two categories: "connected to NSA" (keywords) or "other words". The keywords and their frequency are used to create the bubble chart.
At this point a script, created with the programming language Python, search all the keywords inside each dialogue and, if they appear together, the script creates a line in a chart: the first column (source) is filled with a keyword, and the second one (target) with one other keyword found in the same dialogue. Therefore in the chart a line is created everytime two keywords are together in the same dialogue and each line can appear twice or more, that is everytime the two words are found together in a dialogue. This table is used to create a map with Gephi: each node is a keyword and if two keywords are in the same speech, they are connected with a line.