Posted by Nodus Labs | May 8, 2015
Using Efficient Search Methods for Content Structuring
Designing efficient content structures that guide readers through in ways that are efficient, maintaining diversity and narrative of the original.
Designing efficient content structures that guide readers through in ways that are efficient, maintaining diversity and narrative of the original.
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.
Every year in December Vladimir Putin addresses the Russian Federal Assembly. His address is considered to be a good indicator of the current political mood in the country. Putin’s 2014 speech is especially interesting, because it concerns not only Russia but the whole world. We at Nodus Labs together with Way to Russai analyzed Vladimir Putin’s address made on the 4th of December 2014 using text network analysis and below we present a report on what we discovered. We also made a comparison of the 2014 speech to the 6 speeches before from the years 2008-2013 to see how presidential rhetorics evolved over time.
We could have also called it The Study of Political Manipulation Techniques. This article reveals how the US presidents masterfully used the right rhetorics to address the general sentiment of their voters and set the forthcoming political agenda. Comparative analysis of their inauguration speeches using dynamic text network analysis clearly demonstrates how the importance of various concepts shifts with the new political challenges that the newly elected presidents face.
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