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

Author

Listed:
  • Rui Fan

    (Beihang University)

  • Onur Varol

    (Northeastern University)

  • Ali Varamesh

    (Indiana University)

  • Alexander Barron

    (Indiana University)

  • Ingrid A. van de Leemput

    (Wageningen University)

  • Marten Scheffer

    (Wageningen University)

  • Johan Bollen

    (Indiana University
    Wageningen University
    Indiana University)

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.

Suggested Citation

  • Rui Fan & Onur Varol & Ali Varamesh & Alexander Barron & Ingrid A. van de Leemput & Marten Scheffer & Johan Bollen, 2019. "The minute-scale dynamics of online emotions reveal the effects of affect labeling," Nature Human Behaviour, Nature, vol. 3(1), pages 92-100, January.
    • Handle: RePEc:nat:nathum:v:3:y:2019:i:1:d:10.1038_s41562-018-0490-5
    DOI: 10.1038/s41562-018-0490-5
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    Cited by:

    1. Wang, Chuanbiao & Liu, Ruiying & Wang, Yan, 2023. "The spread dynamics model of the interaction between rumors and derivative rumors in emergencies under the control strategy," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
    2. Jianghao Wang & Yichun Fan & Juan Palacios & Yuchen Chai & Nicolas Guetta-Jeanrenaud & Nick Obradovich & Chenghu Zhou & Siqi Zheng, 2022. "Global evidence of expressed sentiment alterations during the COVID-19 pandemic," Nature Human Behaviour, Nature, vol. 6(3), pages 349-358, March.
    3. Charlotte Out & Martijn Goudbeek & Emiel Krahmer, 2020. "Gradual positive and negative affect induction: The effect of verbalizing affective content," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-20, May.
    4. Jiayin Pei & Zhi Lu & Xiaoming Yang, 2022. "What drives people to repost social media messages during the COVID‐19 pandemic? Evidence from the Weibo news microblog," Growth and Change, Wiley Blackwell, vol. 53(4), pages 1609-1626, December.

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