NetFACS: using network science to understand facial communication systems

Jerome Micheletta; Alexander Mielke; Bridget Waller; Julie Duboscq; Claire Perez; Alan Victor Rincon

NetFACS: using network science to understand facial communication systems

Jerome Micheletta^*, Alexander Mielke, Bridget Waller, Julie Duboscq, Claire Perez, Alan Victor Rincon

^*Corresponding author for this work

Centre for Comparative & Evolutionary Psychology

Research output: Contribution to conference › Abstract › peer-review

Abstract

Understanding facial signals is crucial for understanding the evolution, complexity, and function of the face as a communication system. The Facial Action Coding System enables accurate and objective measure facial movements, but we lack tools to analyse these data and efficiently communicate results. Here, we present ‘NetFACS’, a statistical package combining FACS and network analysis to answer questions about facial communication in humans and other animals.

Original language	English
Pages	5
Number of pages	1
Publication status	Published - 23 Nov 2021
Event	Annual Conference of the Society for Affective Science - Online Duration: 13 Apr 2021 → 16 Apr 2021 https://society-for-affective-science.org/conferences/2021-sas-annual-conference/home/

Conference

Conference	Annual Conference of the Society for Affective Science
Abbreviated title	SAS 2021
Period	13/04/21 → 16/04/21
Internet address	https://society-for-affective-science.org/conferences/2021-sas-annual-conference/home/

Access to Document

Characterisation of facial expressions and behaviours of horses in response to positive and negative emotional anticipation using network analysis
Phelipon, R., Bertrand, L., Jardat, P., Reigner, F., Lewis, K., Micheletta, J. & Lansade, L., 14 May 2025, In: PLoS One. 20, 23 p., e0319315.
Research output: Contribution to journal › Article › peer-review

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NetFACS: NetFACS: Rethinking complexity in facial communication systems
Micheletta, J. (PI), Waller, B. (CoI), Duboscq, J. (CoI), Rincon, A. (Team Member), Perez, C. (Team Member) & Mielke, A. (Team Member)
Leverhulme Trust
1/06/19 → 30/11/22
Project: Research

Cite this

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title = "NetFACS: using network science to understand facial communication systems",

abstract = "Understanding facial signals is crucial for understanding the evolution, complexity, and function of the face as a communication system. The Facial Action Coding System enables accurate and objective measure facial movements, but we lack tools to analyse these data and efficiently communicate results. Here, we present {\textquoteleft}NetFACS{\textquoteright}, a statistical package combining FACS and network analysis to answer questions about facial communication in humans and other animals.",

author = "Jerome Micheletta and Alexander Mielke and Bridget Waller and Julie Duboscq and Claire Perez and Rincon, \{Alan Victor\}",

year = "2021",

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day = "23",

language = "English",

pages = "5",

note = "Annual Conference of the Society for Affective Science, SAS 2021 ; Conference date: 13-04-2021 Through 16-04-2021",

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T1 - NetFACS: using network science to understand facial communication systems

AU - Micheletta, Jerome

AU - Mielke, Alexander

AU - Waller, Bridget

AU - Duboscq, Julie

AU - Perez, Claire

AU - Rincon, Alan Victor

PY - 2021/11/23

Y1 - 2021/11/23

N2 - Understanding facial signals is crucial for understanding the evolution, complexity, and function of the face as a communication system. The Facial Action Coding System enables accurate and objective measure facial movements, but we lack tools to analyse these data and efficiently communicate results. Here, we present ‘NetFACS’, a statistical package combining FACS and network analysis to answer questions about facial communication in humans and other animals.

AB - Understanding facial signals is crucial for understanding the evolution, complexity, and function of the face as a communication system. The Facial Action Coding System enables accurate and objective measure facial movements, but we lack tools to analyse these data and efficiently communicate results. Here, we present ‘NetFACS’, a statistical package combining FACS and network analysis to answer questions about facial communication in humans and other animals.

M3 - Abstract

SP - 5

T2 - Annual Conference of the Society for Affective Science

Y2 - 13 April 2021 through 16 April 2021

ER -

NetFACS: using network science to understand facial communication systems

Abstract

Conference

Access to Document

Fingerprint

Research output

Characterisation of facial expressions and behaviours of horses in response to positive and negative emotional anticipation using network analysis

Projects

NetFACS: NetFACS: Rethinking complexity in facial communication systems

Cite this