Immediate or Reflective?: Effects of Real-timeFeedback on Group Discussions over Videochat

TL;DR

This study introduces an automated videochat system providing real-time feedback on social cues to improve group discussions, showing immediate and lasting effects on participant expressiveness and discussion quality.

Contribution

The paper presents a novel automated framework for real-time social cue analysis and feedback in video discussions, demonstrating its impact on discussion dynamics over multiple sessions.

Findings

Real-time feedback reduces spontaneity during discussions.

Feedback leads to increased expressiveness in subsequent sessions.

System effectively analyzes audio-video cues for social behavior.

Abstract

Having a group discussion with the members holding conflicting viewpoints is difficult. It is especially challenging for machine-mediated discussions in which the subtle social cues are hard to notice. We present a fully automated videochat framework that can automatically analyze audio-video data of the participants and provide real-time feedback on participation, interruption, volume, and facial emotion. In a heated discourse, these features are especially aligned with the undesired characteristics of dominating the conversation without taking turns, interrupting constantly, raising voice, and expressing negative emotion. We conduct a treatment-control user study with 40 participants having 20 sessions in total. We analyze the immediate and the reflective effects of real-time feedback on participants. Our findings show that while real-time feedback can make the ongoing discussion significantly less spontaneous, its effects propagate to successive sessions bringing significantly more expressiveness to the team. Our explorations with instant and propagated impacts of real-time feedback can be useful for developing design strategies for various collaborative environments.