Informative or affective? Exploring the effects of streamers' topic types on user engagement in live streaming commerce

被引:14
|
作者
Luo, Lijuan [1 ]
Xu, Meiling [2 ]
Zheng, Yujie [1 ]
机构
[1] Shanghai Int Studies Univ, Sch Business & Management, Key Lab Brain Machine Intelligence Informat Behav, Minist Educ & Shanghai, Shanghai 201600, Peoples R China
[2] Shanghai Int Studies Univ, Sch Business & Management, Shanghai 201600, Peoples R China
基金
中国国家自然科学基金;
关键词
Live streaming commerce; Social support; User engagement; Text mining; LDA topic modeling; PLATFORMS; BEHAVIOR; TRUST; IDENTIFICATION; PERCEPTION;
D O I
10.1016/j.jretconser.2024.103799
中图分类号
F [经济];
学科分类号
02 ;
摘要
The immense growth of the live streaming industry in the information age has made it a popular and innovative form of information dissemination and entertainment for consumers. Grounding on social support theory, this study uncovers the types of topics discussed by streamers in live streaming commerce and examines their influence on user engagement. Using data from "East Buy", a popular live streaming room in China, we show that speech content of streamers can be categorized into informative and affective topics, and these two types of topics have different effects on users' engagement across behavioral, emotional and relational dimensions. The findings contribute to the existing literature on livestreaming commerce by enhancing our understanding of the informational and emotional support derived from streamers' speech content. Moreover, this study goes beyond a broad concept of user engagement by differentiating it into behavioral, emotional, and relational engagement. By doing so, we extend the current literature on user engagement and investigate how streamers' topic types influence each aspect in the context of live streaming commerce.
引用
收藏
页数:16
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