학술논문

Research on the Uses and Gratifications of Tiktok(Douyin short video)
Document Type
Academic Journal
Source
International JOURNAL OF CONTENTS. 2021-03 17(1):37-53
Subject
Douyin
Uses and Gratifications Theory
Users" preference degree
Use motivation and use satisfaction
Attention intention
Language
Korean
ISSN
1738-6764
2093-7504
Abstract
With the advent of the 5G era, smart phones and communications network technology have progressed, and mobile short video of people"s life can be made, Of the new tools of communication, at present, China"s social short video industry has shown rapid development, and the most representative of the short video app is Douyin (international version: Tiktok). Under the background of Uses and Gratifications Theory, this study discusse the relationship between Douyin users" preference degree, use motivation, use satisfaction and attention intention. This study divides the content of Douyin video into 10 categories, selects the form of an online questionnaire survey, uses SPSS software to conduct quantitative analysis of 202 questionnaires after screening, and finally draws the following conclusions:(1)The content preference degree of Douyin short video (the high group and low group) is different in users" use motivation, users" satisfaction degree and users" attention intention. ALL results are within the range of statistical significance.(2) Douyin users" video content preference degree has a positive impact on users" use motivation, users" satisfaction degree, and users" attention intention. (3) Douyin users" motivation has a positive impact on users" satisfaction and user" attention intention. (4) Douyin users" satisfaction degree has a positive impact on users" attention intention. Based on the research results, we suggest that Douyin platform pushes videos according to users" preferences. In addition, as the preference degree has an impact on users" motivation, satisfaction degree and attention intention of using the platform, it is important that the platform"s focus should to pay attention to the preference degree of users. Collecting users" preferences at the early stage of users" entering the platform is a good way to learn from, and doing a good job of big data collection and management in the later operation.

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