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Social regulation of emotion: messy layers

Overview of attention for article published in Frontiers in Psychology, January 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

blogs
1 blog
twitter
12 X users
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
53 Dimensions

Readers on

mendeley
144 Mendeley
citeulike
2 CiteULike
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Title
Social regulation of emotion: messy layers
Published in
Frontiers in Psychology, January 2013
DOI 10.3389/fpsyg.2013.00051
Pubmed ID
Authors

Arvid Kappas

Abstract

Emotions are evolved systems of intra- and interpersonal processes that are regulatory in nature, dealing mostly with issues of personal or social concern. They regulate social interaction and in extension, the social sphere. In turn, processes in the social sphere regulate emotions of individuals and groups. In other words, intrapersonal processes project in the interpersonal space, and inversely, interpersonal experiences deeply influence intrapersonal processes. Thus, I argue that the concepts of emotion generation and regulation should not be artificially separated. Similarly, interpersonal emotions should not be reduced to interacting systems of intraindividual processes. Instead, we can consider emotions at different social levels, ranging from dyads to large scale e-communities. The interaction between these levels is complex and does not only involve influences from one level to the next. In this sense the levels of emotion/regulation are messy and a challenge for empirical study. In this article, I discuss the concepts of emotions and regulation at different intra- and interpersonal levels. I extend the concept of auto-regulation of emotions (Kappas, 2008, 2011a,b) to social processes. Furthermore, I argue for the necessity of including mediated communication, particularly in cyberspace in contemporary models of emotion/regulation. Lastly, I suggest the use of concepts from systems dynamics and complex systems to tackle the challenge of the "messy layers."

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 144 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 2 1%
France 1 <1%
New Zealand 1 <1%
Belgium 1 <1%
Japan 1 <1%
United States 1 <1%
Poland 1 <1%
Unknown 136 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 28%
Researcher 21 15%
Student > Master 19 13%
Student > Doctoral Student 9 6%
Professor 9 6%
Other 29 20%
Unknown 17 12%
Readers by discipline Count As %
Psychology 75 52%
Social Sciences 12 8%
Neuroscience 9 6%
Computer Science 5 3%
Agricultural and Biological Sciences 5 3%
Other 15 10%
Unknown 23 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 March 2021.
All research outputs
#1,984,138
of 22,696,971 outputs
Outputs from Frontiers in Psychology
#3,901
of 29,445 outputs
Outputs of similar age
#20,439
of 280,682 outputs
Outputs of similar age from Frontiers in Psychology
#206
of 969 outputs
Altmetric has tracked 22,696,971 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 29,445 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 280,682 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 969 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.