Time for Outrage
This body of text that I chose for an analysis with Voyant Tools is from Stéphane Hessel’s book “Time for Outrage.(page 1 to 4) Stéphane Hessel was a member of the Resistance to the Second World War, a diplomat and a writer. In 2010 he published his manifesto “Indignez vous” in which he encourages the younger generations to maintain a power of indignation.
This manifesto is engaged politically and socially.The use of Voyant Tools and in particular the word cloud allows a clearer understanding of the text. Indeed, we see several words that reveal the fundamental ideas of the text as the word ‘resistant’ that is at the heart of the speech of Stéphane Hessel, this word is the most frequently used word: Voyant tells us that it has been used more than 30 times in 4 pages. This allows us to draw a first conclusion, the use of a repeated word can anchor in the memory of the reader, the idea that the author wants to communicate. In a broader vision we also see the words ‘youth’, ‘money‘, and ‘inequality‘, ‘democracy‘ giving us a good idea of the topics that will be discussed.
The illustration of the frequencies shows us the thread of the author’s thought. Thus we can see that the word resistance appears at the beginning of the text blatantly, then that it is the word story that takes over in the last segments. Based on this graph we can therefore correlate the terms.
Nevertheless, we must keep a critical perspective on the use of Voyant. It can be seen that the tool considers words as “to” or “was” as important words in the corpus. Moreover, what is lacking is what software of this type cannot yet never give out is the possibility to understand the ambiguity of words that will not be captured by Voyant.
All the philosophical and positive dimensions of Hessel’s discourse are transcribed schematically and synthetically. The use of a tool like Voyant can allow the rapid understanding of a complex text like that of Hessel and allows us to grasp the main thesis of the author quickly. For all that, can one truly grasp the speech of a man through the machine? This is one of the questions that is raised in the digital humanities.