Data Mining & Quantifying Literature
Chapter seven introduces the idea and significance of quantifying literature through data mining. through quantifying ad data mining we can observe different patterns and analyze data within different texts, articles, books, etc. Different literary resources like Voyant, developed by Geoffrey Rockwell and Stefan Sinclair- which we used in class, allows users to easily distinguish different patterns like different words and how many times throughout the text they were used- along with where in the text you can find said words, recurring phrases, and different themes found in the text. As Quantifying Literature stated, "sometimes the data exposes trends or repetitions that are invisible to a casual reader." With that, identifying and analyzing different patterns and themes allows the reader a fresh, different understanding of literature.
Data mining is the process of analyzing text, video, pictures, and audios and is very important in terms of analyzing different texts. Through data mining, we are able to identify different themes, patterns and other trends embedded in the text (or other form of media.) Data mining can be conducted through a number of different avenues such as- social media response analysis, visualizations through graphs or other methods, or distant reading (which describes the technique of understanding the basis of a text without having to fully read it.)
As previously mentioned, Voyant is a very effective tool in terms of data mining. After pasting your text into the site, it automatically identifies a number of patterns. After pasting my assignment of The False Rhyme by Mary Shelley, you can make several assumptions about the short story- as some of their most frequent terms include "sire" and "said" and "loyalty." With that, we can infer several things about the story- there is a monarch, they use dialogue a lot, and one of the story's themes could be loyalty. While many not see the point in mining and quantifying literature, analyzing different texts allows for readers to develop a deeper understanding of media.
Nice overview of the chapter. When I think of data overview as a whole. I think about how data can tell us a different story than just the read through. Literature seems to always have a certain rhetoric that can be picked up. I think some of these data tools can expose a different side to a work of literature. When we are removed from the passive setting of consuming, we can get a better understanding of the authors choice in the work.
ReplyDeleteThis is a well-written response to the prompt. You effectively highlighted how tools like Voyant can reveal patterns that improve our understanding of literature. I find it fascinating that quantitative analysis can also improve our interpretation especially with themes such as, as you mentioned, loyalty in Mary Shelley's work. This furthers comprehension of aspects that we might miss with traditional reading methods.
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