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Internet Celebrity Economy: Exploring the Value of Viewers’ Comment Features and Live Streamers’
Marketing Strategies in Forecasting Revenue

to the literature on streamer revenue forecasting in live-streaming platforms by proposing
an HB model that captures streamer heterogeneity. Another advantage of the applied HB
model is that we can solve the problem of insufficient sample information and provide
better forecasting accuracy.

7.2 Theoretical Implications
From a theoretical perspective, the contributions of this research are twofold. First,
we contribute to the literature on the emerging social media of live streaming by focusing

on a novel function called paid gifting. Currently, only a few studies on live streaming
have focused on the real behavior of paid gifting, and most of the prior live-streaming
studies have used the perspective of social psychology. Our study is the first to synthesize
an analysis of paid gifting behavior in live streaming from the perspectives of viewers’

comment metrics, discrete emotion-embedded comments, and streamer behavior and
heterogeneity. This study contributes to the literature by demonstrating that the effects of
comment metrics, discrete emotion-embedded comments, and streamers’ behaviors on
viewers’ gift-sending behavior in live streaming are dependent on streamer heterogeneity.

More importantly, this study proves that the conclusions of prior live-streaming studies
may be biased because they ignore the impacts of streamer heterogeneity (e.g., physical
attractiveness, gender, and streamers’ hosting styles).

7.3 Managerial Implications

From a managerial perspective, the purpose of this study is to construct the streamer
revenue forecasting model and examine the effects of viewers’ comment metrics, discrete
emotional comments, and streamers’ characteristics and marketing strategies on gift-

sending behavior in live streaming. The empirical illustrations support the prediction
accuracy of the HB model we propose. Further, the effects of comment metrics, discrete
emotional features, and streamer behavior have implications for live-streaming platforms
in their marketing decision making.
More importantly, they need to reconcile streamer heterogeneity to provide the ideal

live-streaming marketing strategy. In other words, there is no “one size fits all” solution to
live-streaming marketing; its implementation depends on streamers’ personal traits. A male
streamer could focus on chatting with the viewers. A streamer with higher outward beauty

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