Moderating Group Conversation Dynamics with Social Robots

TL;DR

This study explores how social robots can effectively moderate group conversations by using addressing policies to balance attention and reduce subgroup formation, based on data from 300 participants.

Contribution

It introduces a novel robot moderation approach that dynamically manages conversation flow and demonstrates its impact on group interaction balance.

Findings

Robot addressing policy affects conversation balance

Reduces subgroup formation in group discussions

Enhances fairness in participant attention

Abstract

This research investigates the impact of social robot participation in group conversations and assesses the effectiveness of various addressing policies. The study involved 300 participants, divided into groups of four, interacting with a humanoid robot serving as the moderator. The robot utilized conversation data to determine the most appropriate speaker to address. The findings indicate that the robot's addressing policy significantly influenced conversation dynamics, resulting in more balanced attention to each participant and a reduction in subgroup formation.