Proposing the Emotional Consistency Index (ECI): A Quantitative Metric for Emotional Alignment in Cross-Cultural Subtitle Translation

This paper centers on the development and validation of the Emotional Consistency Index (ECI), a novel quantitative metric designed to address a critical gap in translation studies: the lack of tools to measure emotional alignment between subtitled content and audience feedback in cross-cultural transmedia contexts. Traditional subtitle evaluation frameworks prioritize lexical or syntactic accuracy (e.g., BLEU scores, TER), while existing statistical methods (e.g., Pearson’s correlation coefficient) fail to leverage the unique properties of standardized emotional data—undermining their utility for studying how subtitles mediate affect across cultures. Derived from Pearson’s coefficient but simplified to account for the inherent centering of emotional scores (generated via tools like BERT and VADER), ECI streamlines the quantification of emotional resonance while retaining theoretical rigor. Through controlled simulated data experiments, we demonstrate ECI’s ability to distinguish between varying degrees of emotional alignment, validate its computational efficiency, and situate it within translation studies’ broader shift toward transmedia-focused, audience-centric research. This work contributes a practical, theory-driven metric that reorients subtitle evaluation from “linguistic calibration” to the measurement of emotional negotiation—a core dimension of effective cross-cultural communication.