Research Into The Influencing Factors In The Transmission Of Online Videos Of Originality

With stream media being increasingly accessible on mobile devices,online video sharing and watching have become one of the most popular ways by which netizens entertain.It also develops more sophisticated taste,followed by more captious ones,among the audience for the content of videos of different genres.Yet,Bilibili,the domestically reputed video sharing website,caters well to the mass-market in virtue of its unique bullet comments.It authorizes the audience – usually the humorous ones – to re-create the contents by referring to some memes while watching videos.In the meantime,viewers with similar ideas strike the chord with others who have posted similar bullet comments.This type of bullet-comment mode was the first of its kind among domestic video websites.Given the initiative that Bilibili has seized,this paper chooses it as the research object and discusses the factors affecting the transmission of online videos to investigate relevant measures and suggestions.By analyzing relevant theories of Internet information transmission,this paper studies bullet-comment videos from three aspects,including features of the selected videos,of their bullet comments,and uploaders’ characteristics.Python web crawler is used for collecting and processing video information,and the dictionary for sentimental bullet comments and How Net Chinese Emotion Dictionary are employed to mark the texts relating to emotions and to calculate the tendency of those texts after the word segmentation system ICTCLAS is used to classify the text.Following data analysis of descriptive statistics,correlation analysis,variance analysis,multiple linear regression,and factor analysis are the research findings obtained as follows: the number of plays,of comments,and of the bullet-comment videos that are added to favorite playlists exert positive impacts on the transmission of bullet-comment videos;the positive emotional tendency of bullet comments has a negative impact;the number of followers of the uploader and his or her membership level result in positive effects.Based on the findings above,relevant suggestions and measures are put forward.