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

Research output: Journal PublicationArticlepeer-review

3 Citations (Scopus)

Abstract

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
Pages (from-to)435-447
Number of pages13
JournalJournal of Management Analytics
Volume9
Issue number4
DOIs
Publication statusPublished - 2022

Keywords

  • age
  • deep learning
  • dual coding theory
  • live streaming
  • viewer engagement

ASJC Scopus subject areas

  • Statistics and Probability
  • Business, Management and Accounting (miscellaneous)
  • Statistics, Probability and Uncertainty

Fingerprint

Dive into the research topics of 'Effects of age on live streaming viewer engagement: a dual coding perspective'. Together they form a unique fingerprint.

Cite this