“What do you do with a million books?” –Gregory Crane, 2006

“My answer to that question is that whatever you do you don’t read them, because you can’t.” – Tanya Clement

Today, our computers are storing more data than ever and with the progression of ideas such as computer processing and quantum computing it’s no surprise why our scholars need a new way to analyze written text. Thus, digital humanities was born.

The earliest form of digital humanities did not debut until the late 1940’s, which followed the analytics of Roberto Busa on annotating the entirety of Thomas Aquinas’ work. Eventually, after various breakthroughs in the scientific and mathematical world, macro-level analysis was introduced, which included the counting and measuring of data. Although, this quantitative form of analysis was not met without criticism, as scholars complained how “macro-level analysis” failed to create human opinions on data, which made analyzing less humanistic. As a reasonable solution, the term “distant reading”, coined by Franco Moretti, was brought into the world of literature, which allows analyzing larger amounts of written work through close reading of a small number of texts. Next, this blog will cover different types of text analysis and their purpose in the realm of literature and humanities.

Various types of text analysis rule the world of literary studies. Most notably, the use of stylometry, a type that combines the use of statistical analysis and linguistics to study the foundations of text. Next, content based analysis, which studies similarities within a text, such as patterns, repetition of words, and topic trends, with the goal of determining the authenticity of the text. Next, metadata analysis allows the mapping of text by determining factors such as; author, date, and point of origin, to be able to draw comparisons between texts. In conclusion, with the amount of text we’re producing today, humanities scholars must utilize various types of digital text analysis in order to efficiently interpret texts in the largest scale.

Sources

“Text Analysis.” 2016. Tooling Up for Digital Humanities. Accessed August 19. http://toolingup.stanford.edu/?page_id=981.