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/

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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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language = "English",

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

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TY - CONF

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

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NetFACS: NetFACS: Rethinking complexity in facial communication systems

Cite this