Affective Saturation Index: A Lexical Measure of Affect.

Area of Science:

• Psychology
• Computational Linguistics
• Affective Science

Background:

• Affect significantly influences daily life, impacting experiences, psychopathology, and social interactions.
• Traditional affect measurement relies on physiological, self-report, and behavioral methods.
• A need exists for dynamic, context-independent measures of affect intensity.

Purpose of the Study:

• To introduce and validate the Affective Saturation Index (ASI), a novel text-based measure for affect intensity.
• To assess the ASI's convergent and concurrent validity against physiological and linguistic measures.
• To explore the utility of text analysis in quantifying emotional states.

Main Methods:

• Developed the Affective Saturation Index (ASI) based on text analysis principles.
• Collected data from 40 individuals through semi-structured interviews.
• Compared ASI scores with heart rate variability (HRV), Semantic Entropy Index (SEI), and Flesch-Vacca Index (FVI) using ANOVAs and multiple linear regressions.

Main Results:

• The ASI demonstrated construct and criteria validity.
• ASI effectively detected affective saturation in interview transcripts, correlating with SEI (adjusted R² = 0.428) and FVI (adjusted R² = 0.241).
• ASI scores reflected individual affective intensity, correlating with HRV (adjusted R² = 0.428).

Conclusions:

• The ASI provides a valid and reliable method for measuring affect intensity from written text.
• This text-based approach offers a dynamic and context-independent alternative to traditional methods.
• The ASI has potential applications in fields like psychotherapy and social dynamics research.