Project Description
To successfully build the taxonomy, the project will pursue four primary objectives:
Operationalize Proppian Theory for Digital Media: To adapt Vladimir Propp’s 12 core narrative functions (originally designed for 19th-century folklore) into a modern, binary codebook capable of classifying 21st-century political disinformation.
Quantify Disinfolklore Frequencies (RQ1): To determine which specific narrative archetypes (e.g., Villainy, Trickery, False Hero) are most prevalent across a randomized corpus of modern disinformation claims.
Identify Geopolitical Fingerprints (RQ2): To statistically compare the structural taxonomy of foreign state-sponsored campaigns (EUvsDisinfo) against domestic political falsehoods (FactCheck.org) to identify distinct adversary playbooks.
Extract Narrative Templates (RQ3): To identify how individual Proppian functions cluster together sequentially to form highly viral, repeatable narrative blueprints. To maximize efficiency, the methodology utilizes a Converge → Execute → Diverge → Synthesize workflow. Students will start together to ensure data reliability, split the manual labor of coding, diverge into specialized analytical tracks, and reconvene for the final deliverables.
Tasks and Responsibilites
1. Analyze the data for sequential clustering.
2. Using cross-tabulation, the student will map out which functions frequently travel together (e.g., proving that Villainy is almost always followed by a False Hero in Kremlin data).
3. Participate in the team to design the visual layout for their undergraduate symposium presentation, ensuring all three data tracks (Frequencies, Comparisons, and Templates) are represented cohesively.
Desired Qualifications
None listed.