Post #4

Topic 5

I chose to analyse poetry from  Alan Liu’s Data Collections and Datasets and using Voyant to analyse poetry proved effective as it aided to give context to similes and metaphors as well as other poetic devices. Voyant’s ‘context’ section really helped give insight as to what phrases meant and other meanings outside of raw text that wouldn’t have gone unnoticed or misunderstood via close-reading. Voyant also gave insight to how important repetition and key words are in poetry and was easy to interpret using the ‘cirrus’ and ‘trends’ section. Close-reading would have come no where close to the conclusion drawn by Voyant. Voyant uses a number of computer-assisted tools allowing us to covert words into number, qualitative data into quantitative data, this allows for calculation and as well as the use of algorimths. Making it a useful tools when analyse large texts and different styles of literature.

Frequency of words, pointing towards how the author wanted to highlight key terms and establish a theme
Frequency use of words and letters throughout the poem giving insight to use and frequency of poetic devices

This corpus has 1 document with 4,147 total words and 1,139 unique word forms. Created now.

Vocabulary Density: 0.275

Readability Index: 6.456

Average Words Per Sentence: 18.6

Most frequent words in the corpus: like (30); ship (22); ne (19); sea (18); came (17)

(continued) The readability can give us great insight to how effective a text is at conveying it’s goal. Using sources with a high readability index can give website makers an easier time, encapsulating the audience for longer and more effectively. Moreover, the vocabulary density can be used when chosing a targeted audience. Age and education of the audience can be important, and calculating vocabulary density can aid website makers not lose there audience due to high levels of vocabulary complexity (dependent on goal of website).

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