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Exploring user engagement behavior with short-form video advertising on short-form video platforms: a visual-audio perspective

Lin Xiao (Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Xiaofeng Li (Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Jian Mou (School of Business, Pusan National University, Busan, South Korea)

Internet Research

ISSN: 1066-2243

Article publication date: 3 December 2024

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Abstract

Purpose

Short-form video advertisements have recently gained popularity and are widely used. However, creating attractive short video advertisements remains a challenge for sellers. Based on the visual-audio perspective and signaling theory, this study investigated the impacts of three visual features (number of shots, pixel-level image complexity and vertical versus horizontal formats) and two audio features (speech rate and average spectral centroid) on user engagement behavior.

Design/methodology/approach

We conducted a field study on TikTok. To test our various hypotheses, we used regression analysis on 2,511 videos containing product promotion information posted by 60 sellers between January 1, 2020 and November 20, 2021.

Findings

For visual variables, the number of shots and pixel-level image complexity were found to have nonlinear (inverted U-shaped) relationships with user engagement behavior. The vertical video form was found to have a positive effect on comments and shares. In the case of audio variables, speech rate was found to have a significant positive effect on shares but not on likes and comments. The average spectral centroid was found to have significant negative influences on likes and comments.

Practical implications

This study provides specific suggestions for sellers who create short-form videos to improve user engagement behavior.

Originality/value

This study contributes to the literature on short-form video advertising by extending the potential drivers of user engagement behavior. Additionally, from a methodological perspective, it contributes to the literature by using computer vision and speech-processing techniques to analyze user behavior in a video-related context, effectively overcoming the limitations of the widely adopted survey method.

Keywords

Acknowledgements

Funding: This work was supported by a Humanities Social-Science Research Promotion of Pusan National University (2023).

Citation

Xiao, L., Li, X. and Mou, J. (2024), "Exploring user engagement behavior with short-form video advertising on short-form video platforms: a visual-audio perspective", Internet Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/INTR-07-2023-0521

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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