You can have a better overview of any discourse or text if you look at it from the network perspective. If we visualize a text, for example, a Communist Manifesto below, as a graph, the nodes are the words and the connections is a tendency of those words to co-occur together. The more words occur next to each other, the more connected they are, they will form communities. Those communities are indicated with different clusters in the graph and with the colors. The bigger nodes are the more influential ones. These are the words that connect different topics together and are crucial for meaning circulation within the text.

Using the graph below (Communist Manifesto text network visualization), try to identify the most influential terms and topics and how they are connected. Notice the communities of words in different colors and try to remove some of the keywords by clicking on them and then clicking the “trash” button to see how the discourse would change if these terms were not there. This may also indicate how to inject new narrative into this discourse: by addressing the influential nodes (which are not often the most frequently mentioned ones) and the most connected communities (but not necessarily the biggest ones) first.

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