Moderating Group Conversation Dynamics with Social Robots
Lucrezia Grassi, Carmine Tommaso Recchiuto, Antonio Sgorbissa

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.
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Taxonomy
TopicsSocial Robot Interaction and HRI · Multi-Agent Systems and Negotiation
MethodsSoftmax · Attention Is All You Need
