Enthymeme Detection

Enthymemes are arguments with missing premises or conclusions—a classical rhetorical device that reduces cognitive load on the audience by relying on shared assumptions or common sense. Detecting enthymemes computationally is important because they are a persuasion technique used to convey implicit stances in social media, particularly in controversial or political discourse, without explicit assertion that might invite immediate fact-checking.

An enthymeme differs from explicit argument in that the reader must reconstruct the missing component, which creates two vulnerabilities: the unstated premise is harder to scrutinize, and different readers may reconstruct it differently depending on their background knowledge and prior beliefs. This makes enthymemes both a tool for sophisticated persuasion and a source of genuine disagreement in interpretation.

Key papers

• Interpretive Variation and Discourse Structure in Detecting Enthymemes in Controversial Political Discourse — applies transformer-based detection to vaccination and immigration tweets, shows that human disagreement on enthymeme presence is real (not just noise) and proposes metrics to handle it.

Related topics

• Implicit argument detection (recovering missing components)
• Rhetorical analysis (understanding persuasion structure)
• Stance Detection (identifying implicit stances)
• Political discourse (context where enthymemes often appear)