Kaleidoscope: Detecting the Tone of the Room

We aimed to develop a software tool that can determine the “tone of a room” in virtual meetings. Our prototype, Kaleidoscope, uses preexisting machine learning and deep learning libraries to analyze the expressed emotions from individuals in an online meeting, and turn that data into an overall analysis of group tone through novel analytic tools. Results from human participants, asked to identify emotions observed from online meeting videos, are used to validate and refine the prototype. The Kaleidoscope prototype currently achieves an overall accuracy greater than 70%, more than double that of human-to-human agreement; and demonstrates the unique capability of identifying the group tone of a meeting. Future extensions could provide facilitators real-time emotion tracking and group tone assessment, paving the way for technology-assisted interventions to combat group polarization and other problematic group dynamics.

Authors

Institutions

Publication Details

Journal
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Published
2024-08-26
DOI
https://doi.org/10.1177/10711813241260746
Primary Topic
Media Influence and Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Kaleidoscope: Detecting the Tone of the Room

Jennifer McVay, Gillian Baseri, Nate Deml, Scott Warner et al.
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Media Influence and Health
article

Kaleidoscope: Detecting the Tone of the Room

Jennifer McVay, Gillian Baseri, Nate Deml, Scott Warner, Kaitlyn Choy, Victoria Romero
article en

Abstract

We aimed to develop a software tool that can determine the “tone of a room” in virtual meetings. Our prototype, Kaleidoscope, uses preexisting machine learning and deep learning libraries to analyze the expressed emotions from individuals in an online meeting, and turn that data into an overall analysis of group tone through novel analytic tools. Results from human participants, asked to identify emotions observed from online meeting videos, are used to validate and refine the prototype. The Kaleidoscope prototype currently achieves an overall accuracy greater than 70%, more than double that of human-to-human agreement; and demonstrates the unique capability of identifying the group tone of a meeting. Future extensions could provide facilitators real-time emotion tracking and group tone assessment, paving the way for technology-assisted interventions to combat group polarization and other problematic group dynamics.

Proceedings of the Human Factors and Ergonomics Society Annual MeetingVol. 68(1)
CACI International (United States) (US)
Openalex Percentile: Top 79%
Media Influence and Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.