Measuring social support for depression on social media: A multifaceted study on user interaction and emotional spread

Xiao Kun Wu, Yi Yin Zhou, Bu Zhong

Research output: Contribution to journalArticlepeer-review


User interaction within social media groups is increasingly vital for offering social support to individuals experiencing mental health issues. However, measuring social support in these online communities is challenging due to the dynamic and complex nature of user interaction, which conventional research methods struggle to capture. To cope with the challenge, we propose a mixed-measurement approach that combines network theory and social support perspectives to enhance existing measures. Our methods offer a more comprehensive understanding of social support online by estimating emotional spread within these communities and examining the impact of information exposure and government control on community activities and users’ mood stability. Our findings highlight the importance of considering multiple dimensions and factors when measuring social support in social media groups, adding insights into the underlying mechanism of social support cultivation on social media platforms.

Original languageEnglish (US)
Article number102120
JournalTelematics and Informatics
StatePublished - May 2024

All Science Journal Classification (ASJC) codes

  • Communication
  • Computer Networks and Communications
  • Law
  • Electrical and Electronic Engineering

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