Quantifying Emotional Specificity and Ambiguity in Emojis: An Entropy Based Analysis of Discrete Emotion Ratings

Keywords: Emojis, Emotion Specificity Index, Specificity and Ambiguity

Abstract:

Emojis are ubiquitous in digital communication, yet their emotional meanings are
often ambiguous. A recently released normative data set provides mean ratings of
112 emojis on 13 discrete emotions in Spanish speakers. Based on
studies demonstrating that many emoji do not unambiguously depict a single
emotion, we introduce an entropy-based emotion specificity index (ESI)
to quantify how concentrated the ratings of an emoji in one emotion. After
baseline correction, we compute Shannon’s entropy across the 13 emotion
ratings and normalize it by the maximum possible entropy. Low values of ESI
indicate ambiguous or neutral emojis, whereas high values reflect a strong
association with a single emotion. Our analyzes reveal that negative emojis
show greater specificity than positive or neutral ones, that the principal component
analysis recovers a valence continuum explaining nearly 73% of the variance,
and that ESI is systematically related to affective valence. We discuss
applications of the ESI in marketing, health communication, and mental health
monitoring and situate our findings within emerging normative datasets and
cross‑cultural research on emoji interpretation.

Submission Number: 113