"How Did They Come Across?" Lessons Learned from Continuous Affective Ratings

TL;DR

This paper introduces CORAE, a web-based tool for continuous retrospective affect evaluation, analyzing interpersonal perceptions in dyadic interactions to improve understanding of social dynamics and enhance human-robot interaction.

Contribution

The study presents a novel open-source tool and a discourse analysis approach to map interaction events to affect ratings, advancing understanding of dynamic social perceptions.

Findings

Interaction events correlate with complex social phenomena

Affect ratings reflect dynamic and contingent interaction features

Insights support improved human-robot interaction design

Abstract

Social distance, or perception of the other, is recognized as a dynamic dimension of an interaction, but yet to be widely explored or understood. Through CORAE, a novel web-based open-source tool for COntinuous Retrospective Affect Evaluation, we collected retrospective ratings of interpersonal perceptions between 12 participant dyads. In this work, we explore how different aspects of these interactions reflect on the ratings collected, through a discourse analysis of individual and social behavior of the interactants. We found that different events observed in the ratings can be mapped to complex interaction phenomena, shedding light on relevant interaction features that may play a role in interpersonal understanding and grounding. This paves the way for better, more seamless human-robot interactions, where affect is interpreted as highly dynamic and contingent on interaction history.