TY - JOUR
T1 - The secret of voice
T2 - How acoustic characteristics affect video creators' performance on Bilibili
AU - Fu, Shixuan
AU - Wu, Yan
AU - Du, Qianzhou
AU - Li, Chenwei
AU - Fan, Weiguo
N1 - Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2024/4
Y1 - 2024/4
N2 - The importance of voice has been well acknowledged in sensory decision-making. Yet, past literature on video creators' performance did not shed much light on the impact of video creators' acoustic characteristics. Building on signaling theory of portfolios, we examine how the acoustic characteristics of a video creator and the signals of video quantity affect the number of likes a video creator receives and the change in the number of the creator's followers. Using a longitudinal dataset obtained from Bilibili through automated speech recognition analytics and text analysis approach, econometrics models are employed to test the research model. Findings indicate that loudness variability of a video creator significantly increases the number of likes the creator receives, and exerts a positive effect on the change in the number of the creator's followers. In contrast, vocal pitch has a significant positive impact on the number of likes but a significant negative impact on the change in the number of followers. Results further suggest that a video creator's performance varies according to the signals of video quantity, i.e., the number of weekly published videos and the average length of videos. Our results could offer theoretical contributions and practical insights for video creators to enhance their performance by adjusting the acoustic characteristics and the signals of video quantity wisely.
AB - The importance of voice has been well acknowledged in sensory decision-making. Yet, past literature on video creators' performance did not shed much light on the impact of video creators' acoustic characteristics. Building on signaling theory of portfolios, we examine how the acoustic characteristics of a video creator and the signals of video quantity affect the number of likes a video creator receives and the change in the number of the creator's followers. Using a longitudinal dataset obtained from Bilibili through automated speech recognition analytics and text analysis approach, econometrics models are employed to test the research model. Findings indicate that loudness variability of a video creator significantly increases the number of likes the creator receives, and exerts a positive effect on the change in the number of the creator's followers. In contrast, vocal pitch has a significant positive impact on the number of likes but a significant negative impact on the change in the number of followers. Results further suggest that a video creator's performance varies according to the signals of video quantity, i.e., the number of weekly published videos and the average length of videos. Our results could offer theoretical contributions and practical insights for video creators to enhance their performance by adjusting the acoustic characteristics and the signals of video quantity wisely.
KW - Acoustic characteristics
KW - Audio mining
KW - Signaling theory
KW - User-generated video
UR - http://www.scopus.com/inward/record.url?scp=85182399144&partnerID=8YFLogxK
U2 - 10.1016/j.dss.2023.114167
DO - 10.1016/j.dss.2023.114167
M3 - Article
AN - SCOPUS:85182399144
SN - 0167-9236
VL - 179
JO - Decision Support Systems
JF - Decision Support Systems
M1 - 114167
ER -