Text network visualizations are most often used to study and analyze data. However, how can an analytical tool become a musical instrument and what are the implications of that, both for the research process and for the creative work?
In this case study we demonstrate how text network analysis can be used to identify the main topical threads of a conference that consists of several talks. We also show how it can be used to identify how closely those talks are related as well as to suggest collaborations between the speakers or relevant thematic threads for the audience.
In this article we demonstrate how you can visualize Google search results as a network of interrelated terms to identify the most relevant groups of keywords.
Mental disorders and various self-imposed psychological obstacles often arise because of the lack of choice. Gregory Bateson wrote about the double-bind origin of schizophrenic behavior where “crazy” reaction is simply a way of transcending a limiting situation, when the person sees no other choice. Various psychotherapeutic practices focus on expanding the range of possibilities for the patient, offering more choices than is currently available. Text network visualization can be a useful tool to aid this process. In this case study we are going to demonstrate how it works.
Text network analysis can be a very useful tool to make sense of Twitter’s ever-expanding newsfeed. It can be used to visualize a user’s feed of tweets or visualize one’s own newsfeed as a network to be able to see what the tweets are about and how they connect. Text network analysis allows to see not only the main terms, but also how they connect, providing the context to the most relevant keywords found on Twitter.
