Earticle

초록

영어

With the popularization of social media, companies are using it as a new advertising channel to replace traditional advertising channels. As a result, influencer marketing, which utilizes influencers who are highly influential on social media for advertising, is gaining attention. Views are a representative marketing metric, and in this study, we propose a model to predict the number of views of influencer marketing videos using YouTube. To this end, we collected 16,348 influencer marketing videos in the food industry and built a deep learning-based view prediction model using multimodal data such as thumbnails and title text. We also verified the effectiveness of the proposed methodology by performing the same modeling on influencer marketing videos in the tech sector. The results of this study can provide implications for companies and video producers who utilize influencer marketing.

목차

Introduction
Background
Influencer Marketing
Predicting YouTube Video Popularity
YouTube-Based Advertisement
Methods and Experimental Details
Overall Process
Datasets
Data Augmentation
Architecture
Experiment Results
Post-hoc Analysis
Conclusion and Discussion
References
Appendix. A

키워드

저자

• Dongha Kim [ Dept of Library and Information Science, Yonsei University ]
• Juan Yun [ Dept of Industrial & Management Engineering, Korea University ]
• Beomgeun Seo [ Dept of Management Information Systems, Myongji University ]
• Hanjun Lee [ Dept of Management Information Systems, Myongji University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국경영정보학회 정기 학술대회 [KMIS Conference]

• 간기

  반년간

• 수록기간

  1990~2025

• 십진분류

  KDC 325 DDC 658