| The commercialization of 5G has accelerated the Informatization of videos,and the short video market is developing rapidly.The trend of entertainment,knowledge and information acquisition that based on videos is obvious.The creative direction of creators is developing from vertical to diversified,and the audience is extending from young people to all ages,the user browsing content is also expanding to the whole theme.In the context of the COVID-19,popular science videos and online learning of health knowledge have further brought the dissemination of knowledge videos into the public eye,and people have gradually accepted,loved and relied on this way of quickly obtaining effective information in a short period of time.Among many video websites and applications,the layout and rapid development of Bilibili Bullet Screen Video Website(referred to as Bilibili)in the knowledge area is particularly worthy of attention.Knowledge videos work in various fields such as science,law and humanities are very popular at Bilibili.Knowledge videos work usually require higher authenticity,reliability and value,so the threshold for creation is relatively high.At present,there is a clear gap between top and or bottom creators.Research on the influential factors of knowledge videos dissemination will help platforms and creators to better create and disseminate works,and also enable ordinary users to access more positive,valuable and meaningful knowledge information under the background of pan-entertainment of video media.Based on this,this paper conducts a series of studies on the influencing factors of knowledge videos dissemination according to the ideas of analysis,modeling and verification.Firstly,the video communication mode and communication characteristics of the knowledge area of Bilibili are analyzed with the help of the 5 W theory and the uses and gratifications approach.Secondly,the three-tiered model and the elaboration likelihood model are used to calculate the communication effect index and sort out the characteristic dimension of the communication influencing factors respectively.The demonstration of this study was carried out by writing Python crawlers to crawl the popular science plate data in the knowledge area of Bilibili.The influencing factors before and after the dissemination of knowledge videos are studied by logistic regression and multiple regression respectively.And then seven kinds of machine learning algorithms including VotingRegression are combined,key influencing factors were analyzed in the form of feature ranking.And finally,a case is used to explain and verify the qualitative characteristics.In this study,a variety of methods were used to verify the influencing factors of different dimensions of video information,user participation,creators and medias on the transmission of knowledge video,providing a new perspective and new ideas for the study of video transmission and knowledge transmission,as well as relevant management suggestions for creators and platform operators of knowledge videos. |
