Original scientific paper

https://doi.org/10.17559/TV-20190314152108

Hybrid Variable-Scale Clustering Method for Social Media Marketing on User Generated Instant Music Video

Ai Wang ; University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, 100083 Beijing, China
Xuedong Gao ; University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, 100083 Beijing, China

Abstract

Social media has already become one of the mainstream enterprise marketing channels recently. That consists of various media elements, such as text, picture, and even newly developed instant music video etc. Although several text or picture mining techniques could be directly utilized to analyse online user comments, few researches focus on how to improve the marketing performance of social media platforms through a multimedia approach. Therefore, this paper studies the social media marketing problem of user generated instant music video. A hybrid variable-scale clustering algorithm (HVSC) is proposed to analyse user feature through both textual and video content. Combining with the information dissemination characteristics of social media platforms, we also put forth a marketing strategy that intensively enlarges the transmission audience of influential UGC videos. Experiment results show that the HVSC is able to support managers to discover the target potential customer base of each UGC video following their music preference and current interest/concerns. Finally, according to the content relevance and customer influence, the video producers’ incentive mechanism is further discussed.

Keywords

scale transformation; social media mining; user-generated content; video marketing

Hrčak ID:

221003

URI

https://hrcak.srce.hr/221003

Publication date:

12.6.2019.

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