Detecting and Enhancing Intellectual Humility in Online Political Discourse
Samantha D'Alonzo, Rachel Chen, Weidong Zhang, Melody Yu, Jasmine Mangat, Ivory Yang, Weicheng Ma, Martin Saveski, Soroush Vosoughi, Nabeel Gillani

TL;DR
This paper develops methods to measure and improve intellectual humility in online political discussions, demonstrating that targeted interventions can foster more respectful and understanding discourse without decreasing engagement.
Contribution
It introduces a codebook for annotating IH, creates a classifier for large-scale analysis, and empirically shows that online interventions can enhance IH across various political topics.
Findings
More/less IH environments tend to produce similar future posts.
Interventions can successfully increase IH in online discussions.
Enhancing IH does not necessarily reduce user engagement.
Abstract
Intellectual humility (IH)-a recognition of one's own intellectual limitations-can reduce polarization and foster more understanding across lines of difference. Yet little work explores how IH can be systematically defined, measured, evaluated, and enhanced in spaces that often lack it the most: online political discussions. In this paper, we seek to bridge these gaps by exploring two questions: 1) how might preexisting levels of IH influence future expressions of IH during online political discourse? and 2) can online interventions enhance IH across different political topics and conversational environments? To pursue these questions, we define a codebook characterizing different dimensions of IH and intellectual arrogance (IA) and have researchers use it to annotate several hundred Reddit posts, which we then use to develop and validate a classifier to support IH analysis at scale.…
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