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Nostalgia and Online Autobiography: Implications for Global Self-Continuity and Psychological Well-Being

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  • Yuwan Dai

    (Peking University)

  • Qiangqiang Li

    (Binzhou Institute of Technology)

  • Haichun Zhou

    (Beijing Forest University)

  • Tonglin Jiang

    (Peking University)

Abstract

Personal narratives constitute one of the most fundamental means of making sense of one’s experiences. In the digital age, documenting life online has emerged as a new form of personal narrative. However, what contributes to documenting life online and its implications has remained unaddressed. With self-reported scales (Studies 1–2) and the behavioral indicator from social media (i.e., posts on Weibo, a Twitter-like online platform in China; Study 2), we examined the relationship between documenting life online and nostalgia, as well as implications for global self-continuity (i.e., a sense of connectedness among past, present, and future selves) and psychological well-being. We found nostalgia was positively associated with self-reported (Study 1) and behavioral (Study 2) documenting life online. Meanwhile, we also found a sequential mediation model: nostalgia was positively associated with documenting life online. Further, this act of online documentation is sequentially linked to positive impacts on global self-continuity and psychological well-being (Studies 1–2). Theoretical and practical implications were discussed.

Suggested Citation

  • Yuwan Dai & Qiangqiang Li & Haichun Zhou & Tonglin Jiang, 2023. "Nostalgia and Online Autobiography: Implications for Global Self-Continuity and Psychological Well-Being," Journal of Happiness Studies, Springer, vol. 24(8), pages 2747-2763, December.
    • Handle: RePEc:spr:jhappi:v:24:y:2023:i:8:d:10.1007_s10902-023-00701-y
    DOI: 10.1007/s10902-023-00701-y
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    References listed on IDEAS

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    1. 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.
    2. Quyen G. To & Kien G. To & Van-Anh N. Huynh & Nhung T. Q. Nguyen & Diep T. N. Ngo & Stephanie J. Alley & Anh N. Q. Tran & Anh N. P. Tran & Ngan T. T. Pham & Thanh X. Bui & Corneel Vandelanotte, 2021. "Applying Machine Learning to Identify Anti-Vaccination Tweets during the COVID-19 Pandemic," IJERPH, MDPI, vol. 18(8), pages 1-9, April.
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