Friday, January 4, 2019
A Dataset on Black Short Stories
By Kenton Rambsy
The “Black Anthology Project” consists of a dataset charting the large variety of information concerning the publication of short stories by black writers published in approximately 100 collections. I created the dataset as a way of tracking information related to African American short fiction in order to identify what writers and corresponding stories circulate most often in literary anthologies. I also wanted to create a digital record that other researchers could access in order to study the historical contexts in which black short fiction circulates.
Click here to view: The Black Short Story Dataset - Vol. 1
A dataset like this one seeks to address the under-representation of African American subject matter in digital humanities and cultural analytics. Scholars have infrequently sought to compile and analyze data focused on large numbers of black writers. Moreover, scholars have rarely created documents that trace the history of black literature in accessible online formats that other scholars can manipulate and add on to for research purposes.
This dataset can be used to track the circulation histories of approximately 630 unique black short fiction across 100 anthologies. The dataset collections a variety of information, including story titles, original sites of publication, author birth years, and additional information about the authors. The dataset makes it possible to peruse information about 300 authors relatively quickly.
100 anthologies represent a significant but ultimately small portion of the many collections published over the decades. Still, this sample constitutes, I hope, an important step in the direction of producing expansive datasets on the publishing histories of black short stories and African American literary art in general.
• Visualizing the Big 7 – Data Driven Humanities
• Discovering the Big 7: Black short story writers and publishing history
• The Big 7 Tableau Public Visualization
• African American Short Fiction & Data Driven Humanities (MLA)