Archive forOctober, 2011

Semiotic way of interpreting poetry/literature

Step 1
First look at the significant or important words in a page. Think of the meaning for each of the words.

Step 2:
Can the meanings of these words mean anything else? Are there similar words that can be used, but aren’t? What does choosing this word over all the other options do for the poem’s meaning? If a similar word were substituted, would the poem change? If so, what is the significance that this chosen word has?

Step 3:
Continue analyzing the poem through this method to come up with a definition per significant word throughout the poem. Keep in mind that the sounds of words don’t have any meaning and the only significant information is the meaning of the word by comparing to everything the word is not.

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Hover text

How with this rage shall beauty hold a plea,

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The idea of Digital Humanities would fit on Richter’s map. A lot of the tools we have encountered in class largely fall into the “audience” (rhetorical) category. Although Richter mentions that this category has become less popular in the late 18th century, perhaps it has begun to gain more prominence once again. These tools allow readers to see what other readers are thinking or how they are reacting to the text (through discussion type forums), and that input shapes how we see the author trying to create for the audience, allowing us to build a better understanding of the author’s motivations, what we should be taking from the text, and in what ways the author kept in mind traditions or manipulated it to form something new.

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I felt that the last Web Wednesday was a very interesting course because I got a chance to use new tools. The Ngram was the most useful tool that we used because we were able to access hundreds of files and years of books in one compact database. I feel that to be able to analyze a book in statistical or mathematical ways would be useful and could be a new digital humanities tool. The Wordle is similar because it statistically analyzes literature in a smaller scale. Both do things in a more efficient way, although I feel that it isn’t exactly a new tool. It makes the task of counting words in a book more convenient and neat, but I feel that if one needed to analyze word frequency in a book in the past, they would most likely count each word in the book. It would be possible to analyze books statistically before Wordle or Ngram, but definitely much more tedious.


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