Data mining analytics investigation on TikTok users' behaviors: social media app development
ISSN: 0737-8831
Article publication date: 28 October 2022
Issue publication date: 23 July 2024
Abstract
Purpose
TikTok, a social media application (app), was originally positioned as a short music video community suitable for young users, and the app is user-generated content (UGC) short video of vertical music. Users can make their own creative videos. Following the rhythm of the music, users can shoot various video content, personal talents, life records, performances, dances, plot interpretations, etc. However, what are the profiles and preferences of TikTok users, whereby the social media app is mainly developed by UGC? What is the impact of TikTok on the development of social media? In addition, what is UGC's social media model for user interactions in social networks? The purpose of this paper is to address and study these proposed issues.
Design/methodology/approach
All questionnaire items are designed as nominal and ordinal scales (not Likert scale). The obtained data from questionnaires are put into the relational database (N = 2,011). This empirical study takes Taiwan TikTok users as the research object, implements data mining analytics to generate user profiles through clustering analysis and further uses association rules’ analysis to analyze social media apps in social network interaction and social apps’ development by proposing two patterns and several meaningful rules.
Findings
This study finds that social media apps is a valuable practical research topic on online social media development. In addition, besides the TikTok, the authors eagerly await subsequent research to provide more valuable findings of social media apps in both theory and practice.
Originality/value
This study presents the research evidences that social media apps such as TikTok will be able to transcend the current development pattern of social media and make good use of the media and technology innovation of apps in social development and social informatics.
Keywords
Acknowledgements
Funding: This research was funded by the National Science and Technology Council, Taiwan, Republic of China (MOST 111-2410-H-032-017-MY2).
Citation
Liao, S.-h., Widowati, R. and Lee, C.-Y. (2024), "Data mining analytics investigation on TikTok users' behaviors: social media app development", Library Hi Tech, Vol. 42 No. 4, pp. 1116-1131. https://doi.org/10.1108/LHT-08-2022-0368
Publisher
:Emerald Publishing Limited
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