Research on the Motives Affecting the Behavior of Short Video’s Creators

The research on the behavior of short video’s creators is an important part of the research on short video communication mechanism, communication elements, short video public opinion evolution and its development situation prediction. Clarifying the motives that affect the behavior of short video’s creators can achieve the accurate dissemination of short video content, which has a positive significance for the development of the short video industry and has practical value for the network content management department to guide the development of the industry. In the “video communication era”, as a communication carrier, short video has been widely used in e-commerce, government information dissemination and other fields to improve the traditional form of communication, and many good results have already been achieved. However, there are few studies on the origin characteristics of short videos, that is, the motivation of short video’s creators’ behavior. In this article, first, a motivation analysis model of short video’s creators’ behavior is constructed, a questionnaire is used to obtain 2,582 short video’s creators’ behavior, motivation and other characteristic elements, followed by factor analysis, correlation analysis, reliability analysis and other methods to test the authenticity and validity of the variables; second, the stepwise multiple linear regression method is adopted to analyze the dependence relationship between behavior and motivation; finally, through the data analysis results, the degree relationship between the behavior and motivation of the short video’s creator is obtained. The results show that information communication, economic benefits, emotional control, and self-expression are the main motives that affect the behavior of short video’s creators. At the same time, it is found that there is a phenomenon of professional development in short video’s creator groups, and the internal scale of their creations shows the same direction. This research provides new contributions to the establishment of an accurate short video content communication model and the governance of future short video-induced network public opinion.

[1]  Margaret Allman-Farinelli,et al.  Young Adults’ Engagement With a Self-Monitoring App for Vegetable Intake and the Impact of Social Media and Gamification: Feasibility Study , 2019, JMIR formative research.

[2]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[3]  Ed H. Chi,et al.  Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network , 2010, 2010 IEEE Second International Conference on Social Computing.

[4]  A.R.M. Teutle,et al.  Twitter: Network properties analysis , 2010, 2010 20th International Conference on Electronics Communications and Computers (CONIELECOMP).

[5]  Sona Mardikyan,et al.  Analyzing Factors Affecting Users' Behavior Intention to Use Social Media: Twitter Case , 2014 .

[6]  Ralf Herbrich,et al.  Predicting Information Spreading in Twitter , 2010 .

[7]  Chris Evans,et al.  The influence of eWOM in social media on consumers' purchase intentions: An extended approach to information adoption , 2016, Comput. Hum. Behav..

[8]  Utkarsh Ojha,et al.  Not Just a Medical Student: Delivering Medical Education Through a Short Video Series on Social Media , 2019, JMIR medical education.

[9]  Danah Boyd,et al.  Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[10]  Timothy W. Finin,et al.  Why we twitter: understanding microblogging usage and communities , 2007, WebKDD/SNA-KDD '07.

[11]  Krishna P. Gummadi,et al.  Measuring User Influence in Twitter: The Million Follower Fallacy , 2010, ICWSM.