Knowledge Video Communication Effect Based On HSM

With the rapid development of economic level and the sustaining improvement of standards of people’s living,the popularity rate of intelligent equipment continues to rise,at the same time,the knowledge demand of the people also continues to increase.Affected by the normalization of the epidemic,watching videos online has become an important channel for people to acquire knowledge.At the same time,the number of knowledge-based videos on major media platforms has also gradually increased.In recent years,knowledge content on Bilibili has frequently appeared in public view,making more people aware of its diversified learning resources.Therefore,this paper takes Bilibili as a research platform to explore the factors influencing the dissemination effect of knowledge videos,so as to provide references for the platforms and creators of knowledge videos.Firstly,this thesis reviews domestic and foreign literature,builds a research model of influencing factors of video communication effect based on the 5W communication model and the heuristic-systematic model(HSM),and divides heuristic cues into publisher features,title features and cover features.Systematic clues are divided into content theme,video duration,video introduction and video label.The effect of dependent variable video communication is measured by the three dimensions of communication breadth,communication recognition and communication participation,and the transmission breadth was measured by the number of videos played.The number of likes,coins,favorites,and shares was used to measure the spread recognition,Barrage count and comment count measure communication engagement.At the same time,the number of fans is used as the adjustment variable,and the release date is used as the control variable.Secondly,based on the knowledge area of Bilibili video platform as the research background,combined with the Houyi collector and Octopus collector to collect relevant information,title text and cover image of publishers and other data,12301 pieces of sample data were retained after data cleaning,and then feature processing and coding of data were carried out through content analysis.Finally,Data analysis software STATA 17.0 was used to perform descriptive statistics on continuous and categorical variables,multicollinearity test and regression analysis,moderating effect analysis and robustness test on the data to verify the influence of each variable on the video transmission effect.The results showed that the activity and credibility of publishers,title length and emotional tendency,cover characters and subtitles,content features all significantly affected the video communication effect,and the number of fans played a positive moderating role.Contrary to the hypothesis,for example,the activity of publishers has a negative impact on the video communication effect,that is,the more Uploaders contribute,the worse the communication effect;The more video tags there are,the worse the video transmission performance will be.In addition,the video introduction that most Uploaders ignore also plays a key role in video transmission.The results of this study suggest that the platform should play a leading role in promoting public participation in knowledge learning.Uploaders set the title and cover carefully to attract users’ attention,paying attention to the quality of the video content.The Platform and the Uploaders should assist each other to promote the sustainable and healthy development of the platform.