The Edward P. Jones Dataset
Voyant’s various filtering functionalities enabled us to identify and mark key information, like characters, locations, landmarks, and dialogue. We isolated this type of information and exported it into a spreadsheet in order to create an extensive metadata catalogue about each of Jones’s stories. The spreadsheet enabled us to sort various categories and sift through the stories collectively to identify trends and divergences in each story. We were able to document how often certain streets were mentioned and what quadrants most of Jones’s stories were set in as well as what gender characters he presents most often and how often characters speak.
After organizing pertinent information such as the characters’ age and gender; and travel routes and boundaries, we transformed our findings into data visualization graphics. These visualizations are far more inviting and useful in presenting our research findings compared to the densely populated spreadsheets. These interactive charts either map the movement of characters and story settings, provides a comparative analyses the two collections, or provides a gendered analyses of characters in each collection.
Quantifying Jones’s short stories and creating a dataset yielded a plethora of information. The dataset tracks Jones’ strategic use of landmarks. Since Jones’s stories are not set in present day D.C., referencing specific landmarks serves as an indicator giving insight into the decade of each story. The mention of specific landmarks helps readers to gauge what time period the story is set. For instance, Jones mentions Kann’s Department store in several of his stories. The store has been out of business since 1975, and presently the eastern Market Square building now stands on the former Kann's site. Jones’s stories act as a cultural reservoir of sorts by incorporating key locations from distinct periods in D.C.’s geographic history. This type of information helps us to consider the extent to which D.C.’s landscape has changed over several years.
This trove of data not only displayed Jones’ intimate knowledge of D.C.’s historicity and social inner workings, but also his innovation as a prolific author. Stylistic information that emerged from the corpus included the writer’s variations of narrative modes—like the vacillating usage of first or third person narration—across the collections and stories. Distinctions in word counts and types, as well as estimated time periods helped to construct a type of providential scope of the author’s creative mind. Extracting attribute information of the characters introduces the analytical observer to the community, and provides a feel of the author’s proclivities towards certain cast member types—such as gender and age, and in light of their role or amount of speaking parts.
“The Edward P. Jones Dataset,” reveals beneficial patterns within the Washington D.C. geography during a time when the city’s demography divulged a predominately African American or ‘Chocolate’ citizenry. From walking to driving to taking the bus, the data exposed the familial gravity of community which may have been gone unnoticed—at least to this extent—if not for the usefulness of digital methodologies. Eliciting the travel routes and boundaries as well as character demographics from the dataset exemplifies the richness of community in Jones’ D.C., perhaps more than any other aspect of the mined text.