Literature DB >> 30932057

The minute-scale dynamics of online emotions reveal the effects of affect labeling.

Rui Fan1, Onur Varol2, Ali Varamesh3, Alexander Barron3, Ingrid A van de Leemput4, Marten Scheffer4, Johan Bollen5,6,7.   

Abstract

Putting one's feelings into words (also called affect labeling) can attenuate positive and negative emotions. Here, we track the evolution of specific emotions for 74,487 Twitter users by analysing the emotional content of their tweets before and after they explicitly report experiencing a positive or negative emotion. Our results describe the evolution of emotions and their expression at the temporal resolution of one minute. The expression of positive emotions is preceded by a short, steep increase in positive valence and followed by short decay to normal levels. Negative emotions, however, build up more slowly and are followed by a sharp reversal to previous levels, consistent with previous studies demonstrating the attenuating effects of affect labeling. We estimate that positive and negative emotions last approximately 1.25 and 1.5 h, respectively, from onset to evanescence. A separate analysis for male and female individuals suggests the potential for gender-specific differences in emotional dynamics.

Entities:  

Mesh:

Year:  2018        PMID: 30932057     DOI: 10.1038/s41562-018-0490-5

Source DB:  PubMed          Journal:  Nat Hum Behav        ISSN: 2397-3374


  11 in total

1.  Mining Social Media Data for Biomedical Signals and Health-Related Behavior.

Authors:  Rion Brattig Correia; Ian B Wood; Johan Bollen; Luis M Rocha
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2.  Twitter, time and emotions.

Authors:  Eric Mayor; Lucas M Bietti
Journal:  R Soc Open Sci       Date:  2021-05-26       Impact factor: 2.963

3.  Charting the development of emotion comprehension and abstraction from childhood to adulthood using observer-rated and linguistic measures.

Authors:  Erik C Nook; Caitlin M Stavish; Stephanie F Sasse; Hilary K Lambert; Patrick Mair; Katie A McLaughlin; Leah H Somerville
Journal:  Emotion       Date:  2019-06-13

4.  Individuals with depression express more distorted thinking on social media.

Authors:  Krishna C Bathina; Marijn Ten Thij; Lorenzo Lorenzo-Luaces; Lauren A Rutter; Johan Bollen
Journal:  Nat Hum Behav       Date:  2021-02-11

5.  Quantifying societal emotional resilience to natural disasters from geo-located social media content.

Authors:  Krishna Bathina; Marijn Ten Thij; Johan Bollen
Journal:  PLoS One       Date:  2022-06-16       Impact factor: 3.752

6.  Global evidence of expressed sentiment alterations during the COVID-19 pandemic.

Authors:  Jianghao Wang; Yichun Fan; Juan Palacios; Yuchen Chai; Nicolas Guetta-Jeanrenaud; Nick Obradovich; Chenghu Zhou; Siqi Zheng
Journal:  Nat Hum Behav       Date:  2022-03-17

7.  What drives people to repost social media messages during the COVID-19 pandemic? Evidence from the Weibo news microblog.

Authors:  Jiayin Pei; Zhi Lu; Xiaoming Yang
Journal:  Growth Change       Date:  2021-11-15

8.  Quantifying changes in societal optimism from online sentiment.

Authors:  Calvin Isch; Marijn Ten Thij; Peter M Todd; Johan Bollen
Journal:  Behav Res Methods       Date:  2022-03-22

9.  Emotion Naming Impedes Both Cognitive Reappraisal and Mindful Acceptance Strategies of Emotion Regulation.

Authors:  Erik C Nook; Ajay B Satpute; Kevin N Ochsner
Journal:  Affect Sci       Date:  2021-04-20

10.  Depression alters the circadian pattern of online activity.

Authors:  Marijn Ten Thij; Krishna Bathina; Lauren A Rutter; Lorenzo Lorenzo-Luaces; Ingrid A van de Leemput; Marten Scheffer; Johan Bollen
Journal:  Sci Rep       Date:  2020-10-14       Impact factor: 4.379

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