Effects of age on live streaming viewer engagement: a dual coding perspective
Journal of Management Analytics, ISSN: 2327-0039, Vol: 9, Issue: 4, Page: 435-447
2022
- 4Citations
- 13Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
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.
Bibliographic Details
Informa UK Limited
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