Place:Alderman Library, Rm 421
Registration:Required! Details below.
Hope you had a restful holiday season! The Scholars’ Lab is getting back into the swing of things, and we wanted to invite you all to an upcoming presentation by our 2018-2019 Digital Humanities Prototyping Fellows. These students each received funding from us to work with on building out a proof-of-concept digital humanities project related to their research. The event will take place on Tuesday, January 22nd from 10:30-1:00PM in Alderman 421. The presentations will take place roughly from 10:30-12:00PM and lunch will follow for attendees. You’re free to come late or leave early as your schedule demands.
Our presenters will be Alyssa Collins, Christian Howard, and Sarah McEleney. Alyssa and Christian are both PhD students in the English department, and they will be presenting on a joint project related to using Twitter data in literary research. Sarah is a PhD student in Slavic Languages and Literatures, and she will be presenting on a text analysis project analyzing socialist realism literature.
Full abstracts and bios can be found below. We hope to see you there!
Alyssa Collins and Christian Howard
Our project, titled Twitterature: Methods and Metadata, seeks to outline a methodology for practically using Twitter data in literary research. Our project is interested in two specific aspects of Twitter: the use of Twitter as a publication platform and the collection of tweets into corpora based on keywords [based on hashtag communities?]. As a publication platform, Twitter unsettles traditional publication methods and reaches a wider audience that is not bound by national and linguistic borders. Twitter is thus creating a new kind of ephemeral, digitally-global literature. Additionally, we understand hashtags as metadata that allows us to collect various corpora related to specific places, events, or communities. We’re then able to analyze these communities for linguistic tricks influences. Our project uses Python to scrape Twitter, Twarc tools developed by DocNow to filter and organize the results, and tools such as ArcGIS and visual networking platforms to visualize the results.
Alyssa Collins is a Ph.D. candidate in the English department of the University of Virginia and a 2016-17 Praxis fellow in the digital humanities. Her dissertation “Racing the Posthuman: Examining Representations of Technological and Virtual Embodiment” looks at the intersections of race and technology as depicted in 20th century and contemporary African American literature, digital culture, and new media. When she’s not writing her dissertation she writes about race, superheroes, and embodiment around the Internet.
Christian Howard is a PhD Candidate in English at the University of Virginia and the current project manager for the DH@UVA Curriculum Development Team. Her dissertation, titled “Radical Translation: The Ethics of World Literature,” reconceptualizes world literature through advancements in digital humanities and explores how we can ethically connect to one another through online spaces.
The state-prescribed genre of socialist realism defined, to a certain extent, mainstream literature in the Soviet Union, especially during the Stalin era. Based on the idea that the main purpose of literature was to serve the state and promote communist ideology, Soviet writers were expected to embed the principles of ‘ideological commitment’ (ideinost’), ‘party-mindedness’ (partiinost’), and ‘popular spirit’ (narodnost’) into their socialist realist literary works. In the harsh Stalinist political climate in the 1930s, adhering to socialist realist doctrine became almost mandatory for writers working with the state publishing houses and journals, particularly after the First Congress of Soviet Writers in 1934, which declared socialist realism as the official genre for Soviet writers. However, definitions of socialist realism were often vague and varied, with interpretations differing among assorted critics and authorities. Thus, pinpointing the distinct characteristics of socialist realist is not an easy task, as it was a dynamic genre that changed over Soviet history and was manifested differently in the work of different Soviet authors.
With this is mind, can a modern text analysis/natural language process approach to socialist realism retrospectively shed new light on the attributes of this uniquely Soviet genre? What new information can topic modeling and text analysis approaches offer regarding the particularities of socialist realist prose in the early Soviet Union, and can this tell us something about the nature of ideologically-motivated literature and early Soviet cultural history? This project utilized Python and various available libraries within it to conduct an analysis of the linguistic and topical attributes of early Soviet socialist realist literature, with particular emphasis on Stalin-era literature.
Sarah McEleney is Ph.D. candidate in Slavic Languages and Literatures at The University of Virginia. Her interests include the history of literature in the Soviet Union, digital humanities and data science approaches to the study of literature, and the Polish, Russian, and Ukrainian languages. She is a prior Praxis fellow in the Scholars’ Lab and recipient of the Presidential Fellowship in Data Science at The University of Virginia.
Contact Scholars' Lab's Head of Public Programs Laura Miller.