A Computational Model for Simultaneous Employment of Multiple Emotion Regulation Strategies

Bas Chatel; Atke Visser; Nimat Ullah

doi:10.1007/978-3-030-59277-6_20

A Computational Model for Simultaneous Employment of Multiple Emotion Regulation Strategies

Bas Chatel, Atke Visser, Nimat Ullah^*

^*Corresponding author for this work

Computer Science

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Emotion regulation plays a major role in everyday life, as it enables individuals to modulate their emotions. Several strategies, for regulating emotions, can be used individually or simultaneously, such as suppression, rumination, acceptance, problem-solving, self-criticism, and experiential avoidance. This paper presents a temporal causal network model that simulates the employment of these seven emotion regulation strategies by a person experiencing varying intensity of anxiety. Simulation results are reported for both, the high and low, emotional intensity where the level of activation of these strategies vary with the intensity of negative emotions.

Original language	English
Title of host publication	Brain Informatics
Subtitle of host publication	13th International Conference, BI 2020, Padua, Italy, September 19, 2020, Proceedings
Editors	Mufti Mahmud, Stefano Vassanelli, M. Shamim Kaiser, Ning Zhong
Publisher	Springer Nature Switzerland AG
Pages	217-226
Number of pages	10
ISBN (Electronic)	9783030592776
ISBN (Print)	9783030592769
DOIs	https://doi.org/10.1007/978-3-030-59277-6_20
Publication status	Published - 2020
Event	13th International Conference on Brain Informatics, BI 2020 - Padua, Italy Duration: 19 Sep 2020 → 19 Sep 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12241 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th International Conference on Brain Informatics, BI 2020
Country/Territory	Italy
City	Padua
Period	19/09/20 → 19/09/20

Keywords

Acceptance
Cognitive reappraisal
Emotion regulation
Experiential avoidance
Expressive suppression
Problem-solving
Rumination
Self-criticism
Temporal causal network modeling

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Chatel, B., Visser, A., & Ullah, N. (2020). A Computational Model for Simultaneous Employment of Multiple Emotion Regulation Strategies. In M. Mahmud, S. Vassanelli, M. S. Kaiser, & N. Zhong (Eds.), Brain Informatics: 13th International Conference, BI 2020, Padua, Italy, September 19, 2020, Proceedings (pp. 217-226). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12241 LNAI). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-59277-6_20

Chatel, Bas ; Visser, Atke ; Ullah, Nimat. / A Computational Model for Simultaneous Employment of Multiple Emotion Regulation Strategies. Brain Informatics: 13th International Conference, BI 2020, Padua, Italy, September 19, 2020, Proceedings. editor / Mufti Mahmud ; Stefano Vassanelli ; M. Shamim Kaiser ; Ning Zhong. Springer Nature Switzerland AG, 2020. pp. 217-226 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A Computational Model for Simultaneous Employment of Multiple Emotion Regulation Strategies",

abstract = "Emotion regulation plays a major role in everyday life, as it enables individuals to modulate their emotions. Several strategies, for regulating emotions, can be used individually or simultaneously, such as suppression, rumination, acceptance, problem-solving, self-criticism, and experiential avoidance. This paper presents a temporal causal network model that simulates the employment of these seven emotion regulation strategies by a person experiencing varying intensity of anxiety. Simulation results are reported for both, the high and low, emotional intensity where the level of activation of these strategies vary with the intensity of negative emotions.",

keywords = "Acceptance, Cognitive reappraisal, Emotion regulation, Experiential avoidance, Expressive suppression, Problem-solving, Rumination, Self-criticism, Temporal causal network modeling",

author = "Bas Chatel and Atke Visser and Nimat Ullah",

year = "2020",

doi = "10.1007/978-3-030-59277-6_20",

language = "English",

isbn = "9783030592769",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Nature Switzerland AG",

pages = "217--226",

editor = "Mufti Mahmud and Stefano Vassanelli and Kaiser, {M. Shamim} and Ning Zhong",

booktitle = "Brain Informatics",

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Chatel, B, Visser, A & Ullah, N 2020, A Computational Model for Simultaneous Employment of Multiple Emotion Regulation Strategies. in M Mahmud, S Vassanelli, MS Kaiser & N Zhong (eds), Brain Informatics: 13th International Conference, BI 2020, Padua, Italy, September 19, 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12241 LNAI, Springer Nature Switzerland AG, pp. 217-226, 13th International Conference on Brain Informatics, BI 2020, Padua, Italy, 19/09/20. https://doi.org/10.1007/978-3-030-59277-6_20

A Computational Model for Simultaneous Employment of Multiple Emotion Regulation Strategies. / Chatel, Bas; Visser, Atke; Ullah, Nimat.

Brain Informatics: 13th International Conference, BI 2020, Padua, Italy, September 19, 2020, Proceedings. ed. / Mufti Mahmud; Stefano Vassanelli; M. Shamim Kaiser; Ning Zhong. Springer Nature Switzerland AG, 2020. p. 217-226 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12241 LNAI).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AU - Chatel, Bas

AU - Visser, Atke

AU - Ullah, Nimat

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N2 - Emotion regulation plays a major role in everyday life, as it enables individuals to modulate their emotions. Several strategies, for regulating emotions, can be used individually or simultaneously, such as suppression, rumination, acceptance, problem-solving, self-criticism, and experiential avoidance. This paper presents a temporal causal network model that simulates the employment of these seven emotion regulation strategies by a person experiencing varying intensity of anxiety. Simulation results are reported for both, the high and low, emotional intensity where the level of activation of these strategies vary with the intensity of negative emotions.

AB - Emotion regulation plays a major role in everyday life, as it enables individuals to modulate their emotions. Several strategies, for regulating emotions, can be used individually or simultaneously, such as suppression, rumination, acceptance, problem-solving, self-criticism, and experiential avoidance. This paper presents a temporal causal network model that simulates the employment of these seven emotion regulation strategies by a person experiencing varying intensity of anxiety. Simulation results are reported for both, the high and low, emotional intensity where the level of activation of these strategies vary with the intensity of negative emotions.

KW - Acceptance

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Chatel B, Visser A, Ullah N. A Computational Model for Simultaneous Employment of Multiple Emotion Regulation Strategies. In Mahmud M, Vassanelli S, Kaiser MS, Zhong N, editors, Brain Informatics: 13th International Conference, BI 2020, Padua, Italy, September 19, 2020, Proceedings. Springer Nature Switzerland AG. 2020. p. 217-226. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2020 Sep 15. doi: 10.1007/978-3-030-59277-6_20

A Computational Model for Simultaneous Employment of Multiple Emotion Regulation Strategies

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