Persuasion Index: A Theory-Guided Framework for Persuasion Analysis

2026-06-12

AI Summary

This study addresses the challenges of information manipulation and aims to enhance AI safety and public health communication by proposing a 15-dimensional Persuasion Index (PI) grounded in psychological and communication theories. The framework leverages 55 lexicon- and rule-based subfeatures to construct a lightweight, interpretable, and modular system for assessing persuasiveness, featuring flexible component substitution, an open-source toolkit, and a visualization interface. Experimental evaluation across four heterogeneous datasets demonstrates that PI achieves both computational efficiency and strong predictive performance, uncovering cross-domain commonalities as well as topic-specific associations between persuasive dimensions and outcome variables. This work establishes a novel paradigm for transparent and auditable analysis of human–AI communication.

Abstract

Identifying persuasive rhetorical cues is critical across domains, from detecting information manipulation and improving AI safety to advancing public health communication. We propose Persuasion Index (PI), a taxonomy of 15 dimensions grounded in persuasion theories from psychology and communication, and one transparent implementation using 55 sub-features built from lexicons and rule-based detectors. The taxonomy is modular: individual detectors can be replaced while preserving the theoretical structure. By evaluating PI on four public datasets varying in domain, style, and outcome measures, we show that PI provides a shared feature space for interpreting rhetorical patterns associated with persuasion-related outcomes. Linear models show that PI features carry meaningful predictive signal while remaining computationally lightweight. Dimension-level analyses reveal recurring associations between PI dimensions and persuasion outcomes across datasets, while also highlighting topic- and stance-specific variation. We release PI as an open-source package and web interface for principled and auditable analysis of human and AI-mediated communication.

Problem

• persuasion
• rhetorical cues
• information manipulation
• AI safety
• public health communication

Innovation

• Persuasion Index
• theory-guided framework
• modular taxonomy
• rule-based detectors
• interpretable features