Effects of Age on Live Streaming Viewer Engagement: A Dual Coding Perspective

Fei Liu, Yijing Li, Xiaofei Song*, Zhao Cai, Eric T.K. Lim, Chee-Wee Tan

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review


Though the emerging live streaming industry has attracted growing attention, the dominant yanzhi category where streamers mostly interact with the audience through amateur talent shows and casual chats has not been widely investigated. To decode the mechanism behind the popularity of yanzhi streamers, this study draws on Dual Coding Theory (DCT) to posit that age estimated from a streamer’s face and voice can influence the level of viewer engagement. To validate our hypothesized relationships, 274 one-minute video records ahead of a viewer commenting or/and gifting were collected and analyzed via deep learning algorithms. Analytical results attest to the negative effects of both facial and vocal age on viewer engagement, while their interaction has a positive impact on viewer engagement.
Original languageEnglish
JournalJournal of Management Analytics
Issue number4
Pages (from-to)435-447
Number of pages13
Publication statusPublished - Dec 2022


  • Live streaming
  • Age
  • Viewer engagement
  • Dual coding theory
  • Deep learning

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