Research On The Relationship Between Users And Content Of Algorithmic Recommendation Media

With the rapid development of Internet technology,the algorithm recommendation mechanism has changed the content production,review and distribution of information-based algorithm media.Algorithm recommendation mechanism has a great impact on users and content.However,while achieving accurate match between users and content,it also produced cocoon room effects and the platform blindly pursued flow,resulting in low quality content.Under the algorithm recommendation mechanism,what is the relationship between media users and content? How do users and content respond to each other? What is the essence?What are the attributions? How to govern? These are questions worthy of investigation.However,there has not been any academic research on information-based algorithmic media in this regard up to now.As a typical representative of the sinking market information algorithm media,Qu Toutiao also used the algorithm recommendation mechanism to achieve the match of users and content.It has the ability to carry out technology research and development independently and it has a platform to collect users' data.Therefore,this article took Qu Toutiao as an example to analyze the response relationship between users and content under the algorithm recommendation mechanism.In the first part,this article studied the technical context of algorithmic media and established the framework of algorithm recommendation mechanism.It is clear that data is the core of algorithm recommendation mechanism.The essence of algorithm recommendation mechanism is to achieve match between user and content.In the second part,a questionnaire for users was designed with the Qu Toutiao as the analysis sample,and the content was sampled to analyze the response relationship between users and content under the algorithm recommendation mechanism.Firstly,the content analysis category of Qu Toutiao was constructed from five dimensions of content source,content type,content structure,content sentiment dimension and content feedback,and a detailed quantitative analysis was performed on the content sample.Secondly,the users' response to the content was analyzed from three aspects which were user attributes,demand motivation and demand behavior.Then,the content response to the users' needs was analyzed from two aspects of positive content response and negative content response.Finally,the essence of therelationship between media users and content under the algorithm recommendation mechanism was summarized.In the third part,the universality of the negative response relationship between media users and content under the algorithm recommendation mechanism was analyzed.The reasons were conducted and governance suggestions were proposed.This article took Qu Toutiao as an example to analyze the response relationship between users and content under the algorithm recommendation mechanism,which can provide inspiration and reference for other similar information algorithm media to promote the sustainable development of informational algorithmic media.